RNA microarrays and RNA-seq are nowadays standard technologies to study the transcriptional activity of cells. Most studies focus on tracking transcriptional changes caused by specific experimental conditions. Information referring to genes up- and downregulation is evaluated analyzing the behaviour of relatively large population of cells by averaging its properties. However, even assuming perfect sample homogeneity, different subpopulations of cells can exhibit diverse transcriptomic profiles, as they may follow different regulatory/signaling pathways. The purpose of this study is to provide a novel methodological scheme to account for possible internal, functional heterogeneity in homogeneous cell lines, including cancer ones. We propose a novel computational method to infer the proportion between subpopulations of cells that manifest various functional behaviour in a given sample. Our method was validated using two datasets from RNA microarray experiments. Both experiments aimed to examine cell viability in specific experimental conditions. The presented methodology can be easily extended to RNA-seq data as well as other molecular processes. Moreover, it complements standard tools to indicate most important networks from transcriptomic data and in particular could be useful in the analysis of cancer cell lines affected by biologically active compounds or drugs. RNA microarrays and RNA-seq are one of the most popular high-throughput methods used in the advanced medical diagnostics, personalized medicine, and basic research. Although an application of these methods provides an insight into the full transcriptome of examined sample, the knowledge gained in this way is based upon an averaged gene expression in a bulk population. This fact introduces a specific bias into the outcome of gene expression measurements, especially, because a biological material is rarely homogeneous. A sample heterogeneity is either due to the diversity of cell types in case of tissue samples, or due to minor gene expression differences in samples obtained from cell lines. In both cases an observed average expression level may conceal relevant, cell-specific properties or mechanisms activated only in subpopulations of cells , 2. TherA closely related topic refers to the reconstruction of gene regulatory networks from mRNA expression data. A plethora of methods were proposed, but none of them brought a spectacular success. In particular, Zhang et al.  presenteHere, we decided to explore the already existing knowledge on the regulome and the signalome to provide an insight into the heterogeneity of molecular processes in a cell population under study. Therefore, the proposed methodology complements the above-mentioned procedures for inferring gene regulatory networks. Our method explores the functional heterogeneity of a given cell population sample through the quantification of the intensity of molecular processes occurring in it. in vitro experiments. The first one was aimed to assess the global transcriptomic changes occurring in the ovarian cancer cell line SKOV3 upon paracrine signaling present in the peritoneal cavity. The second one was aimed to decipher how the ceramide induced pathways are affected by the inhibition of poly(ADP-ribose) polymerase (PARP) in the neuroblastoma cell line SH-SY5Y. In both test-case studies the MPH method was used on microarray expression data to estimate the changes in the viability of variously treated populations of cells. The obtained computational predictions were validated with the results of additional wet-lab assays.The proposed approach was tested using the data from two independentThe paper is organized as follows. In the next section we present the workflow of the MPH method and validation strategies that are applied. Materials and Methods contains the description of the biological experiments and the detailed presentation of the computational method. In Results an insight into the final outcomes from the MPH method is provided and in Discussion we elaborate about the compatibility of computational and experimental results as well as the method effectiveness. Finally, in Conclusions we summarize our work and point out the future steps that we plan to undertake.Our goal is to estimate the proportion of different cell subpopulations existing in the analyzed sample being a type-homogeneous population of cells. We assume that there exist at least two different molecular processes manifested by different transcriptional activity of a specific cell subpopulation. Specifically, the proportion should be understood as a qualitative contribution of each subpopulation into the transcriptomic signal observed in the data retrieved from the whole sample.Along with the proportions, we determine transcription patterns specific for each subpopulation. Again, it should be mentioned that values assigned to the expression of each gene in the patterns are not strictly levels of transcription, but rather correspond to the trends observed in detected subpopulations. The MPH method described below was validated using the gene expression data from two case studies described in detail in Materials and Methods.To quantify the composition of the sample, we adapted the computational framework designed originally for the deconvolution of a gene expression matrix from heterogeneous samples . The metThe procedure starts with the routine processing of the raw data from the microarray experiments resulting in normalized, filtered  expressions for each experimental scenario. Then, for the further analysis we select only these genes that differentiate the experimental conditions in the considered study in a statistically significant manner.DSection algorithm  [The next step is the  method) . It requ method) , to finassKL which is a modified version of the algorithm proposed in [The lists of marker genes are used as an input to the second decomposition phase called posed in . The out in vitro wet-lab assay . Finally, marker genes from the previous step were assessed to find out whether they characterize specific functions.Results of this step are validated using the dedicatedThe MPH framework was used to verify two hypotheses that were addressed in the conducted experiments. First, we want to assess and compare the putative paracrine influence of K21 fibroblasts and SKOV3 cells on ovarian cancer cell proliferation. It is presumed that, despite serum-free conditions, secretion products of both cell types are able to prompt SKOV3 cell divisions and that the stromal signaling exerts a stronger effect.In the second case, we want to computationally quantify the influence of PJ34-PARP inhibitor on the viability of the C2-ceramide treated cells. The hypothesis claims that PJ34 poses a cytoprotective character. For detailed description of the biological background of both case studies see Finally, thanks to our approach that determines function-specific transcriptomic profiles, we provide the most important markers characterizing concrete cellular functions. Here, it should be emphasized that the knowledge about gene regulation in cancerous cells is still quite vague and selection of novel biomarkers for specific cellular processes might improve our understanding of cancer development mechanisms.2.The ovarian cancer cell lines SKOV3 (HTB-77) and the human neuroblastoma cell line SH-SY5Y were obtained from American Type Culture Collection (ATCC); healthy fibroblast cell line K21 was a gift from Dr. Barbara Tudek . Cells were maintained at 37°C in a humidified incubator containing 5% COCase Study 1. SKOV3 and K21 cells were cultivated in a high glutamine RPMI (Cytogen), supplemented with 10% FBS (Cytogen), 20 mM HEPES (Cytogen), and 1% Penicillin-Streptomycin solution (Cytogen). To obtain conditioned media, cells were cultivated up to 80% confluence, washed three times with PBS solution, and incubated in the serum-free culture media. Following the 72-hour growth, the conditioned media (CM) were collected and filtered  to remove cellular debris.Case Study 2. The SH-SY5Y (Sigma-Aldrich) cells were cultured in MEM/F-12 Ham Nutrient Mixtures (1 : 1) (Biowest) supplemented with 15% heat-inactivated FBS (Cytogen), 1% penicillin/streptomycin, and 2 mM glutamine (Sigma-Aldrich). Prior to treatment, the cells were cultivated in low serum medium (2% FBS).Case Study 1. For the microarray experiments, SKOV3 cells were cultured up to 70% confluence, washed twice with PBS, and incubated for 48 hours in media conditioned by SKOV3 cells (CM-SKOV3) or K21 (CM-K21). Following CM culture, mRNA was isolated using Trizol reagent followed by DNase treatment (Roche) and purification using RNAeasy extraction kit from Qiagen. Samples of 200 ng of total RNA were analyzed on Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. We analyzed three RNA samples per condition.Case Study 2. SH-SY5Y cells were cultivated for 3, 6, and 24 hours in the following experimental settings supplied with (i) 25 μM C2-ceramide d18:1/2:0 (Enzo Life Sciences); (ii) 25 μM C2-eramide d18:1/2:0 (Enzo Life Sciences) and 20 μM PARP-1 inhibitor PJ-34 (Sigma-Aldrich); (iii) pure medium for control samples. The experiment was done in three replicates. After 3, 6, and 24 hours of cultivation cells were collected and RNA was purified using Affymetrix PrepEase RNA Spin Kit. The whole-transcript analysis was conducted using Affymetrix Human Gene 2.1 ST Array Plates.https://www.qiagen.com/ingenuity, IPA®, Qiagen Redwood City).Gene lists were annotated and analyzed using Qiagen's Ingenuity Pathway Analysis tools (Case Study 1. Cell proliferation was performed in six repeats by Resazurin (Sigma-Aldrich) Reduction Assay. Briefly, 2000 SKOV3s/well were seeded in 96-well plate. Following treatment for the indicated time, 10 μl of 0,01% resazurin solution was added to each well and incubated at 37°C for up to 72 h. The fluorescence was measured at different time points with a Multimode Microplate Readers (BioTek) at a wavelength of 590 nm. Proliferation curves were analyzed using GraphPad Prism software .Case Study 2. After treating SH-SY5Y cells with different compounds, cell viability was evaluated using 2--2,5-diphenyltetrazolium bromide assay . Representative samples were collected from each experimental setting, MTT was added to all of the wells. The cells were incubated at 37°C for 2 h, followed by cell lysis and spectrophotometric measurement at 595 nm.X  into the product of two matrices W and H of given rank k (the rank corresponds to the number of expected cell types in a sample): W is a matrix with a cell-specific transcriptome (rows represent genes and each column corresponds to one of the expected cell types), H is a matrix with proportions of cells in each sample , and ϵ models the error/noise.In our work we applied the matrix deconvolution algorithms that originally were used in the analysis of heterogeneous samples being composed of different cell types in some proportions. In general, these methods cover a wide range of approaches which try to decompose a gene expression matrix DSection and ssKL. DSection algorithm [In this study we are especially interested in two algorithms: lgorithm  is an unJ cell-type homogeneous samples; in each sample T cell subpopulations are involved in different molecular processes and C experimental conditions. For each sample j the a priori knowledge pj =  about proportions of cells with specific function is also given. Then the expression yij of the ith gene in jth sample is described as xi,c(j) = 1,,…, xT,i,c(j)) represents the contribution of different cell subpopulations  to the observed ith expression profile and ϵi,j is a normally distributed noise reflecting replication noise with variance 1/λi, for some constant λi. Hence, the likelihood of yi,j can be described as λi, is heteroscedastic across probes and homoscedastic across cell subpopulations and experimental conditions. Finally, assuming i.i.d. measurements  a factorized form for the joint data (𝒟) likelihood can be written as θ represents all model parameters; that is, θ = . More detailed description of prior specifications, sampler construction, and posterior sampling, that is, probability of acceptance of one step in constructed mixed Gibbs and Metropolis-Hastings sampler, can be found in [In the context of our problem, assume we have found in .ssKL is an approach that is based on iteratively computed approximation of a desired decomposition. In our case it is supported by a list of marker genes characterizing molecular functions that are active in the sample of interest and regulate its observed transcriptome. Specifically, the factorization X ~ WH, given a desired rank k , starts with a random initialization of W and H matrices which are then updated to minimize a divergence functional:On the other hand, run  was performed using DAVID tool , 12. It In the first case study we end up with the marker genes for (i) the proliferation activity composed of 12 genes, CDC20, TK1, KNL1, CENPE, STIL, ANLN, NDC1, NUF2, KIF20A, PLK4, CCNB1, and CCNA2, and (ii) the quiescence state composed of 12 genes: COL5A1, TGFBI, TCEA2, WNT9A, MMP11, LAMB1, KRT14, LTBP1, PHLDB1, TIMP3, LRP1, and COL18A1.On the other hand, in the second case the following marker genes are described: (i) proliferation regulation including 11 genes, CD24, NRP1, TNS3, MYC, CD38, CCNA2, FGF7, MST1R, MYCN, ETS1, and EDNRA, and (ii) cell death related regulation including 12 genes: DDIT3, ERN1, JUN, SQSTM1, SMPD1, TGFB1, PRNP, CEBPB, NQO1, NR4A1, CTSB, and ZMAT3.ssKL step. It turned out that a set of 10–12 genes is sufficient to keep the percentage results robust. Moreover, we verified how the average fold change of selected marker genes influences the final predicted proportions in the ssKL algorithm; see The expression patterns of all selected marker genes can be investigated in ssKL method to predict the final proportion of different cell activities in the analyzed samples. In both case studies we observed significant differences in fractions of cells exhibiting investigated behaviours . In each experimental condition H0 was rejected in favor of H1  fits the data better than the hypothesis assuming homogeneous population . The statistics for the most influenced functions reported in this section are listed in The additional validation of our results was performed using the classical approach to the functional analysis of transcriptomic data. We intend to verify if profiles detected by application of the MPH method are consistent with general, average tendencies indicated by functional analysis tools. In order to identify molecular and cellular functions altered by treatments we performed core analysis using Ingenuity Pathway Analysis tool p value and cut off the number to 2238 based on the fold change. In the second case 3983 genes were selected for further analysis as distinguishing three experimental conditions, that is, control, C2-ceramide treated, and both C2-ceramide and PJ34 treated.In the first case study we selected 3946 differentially expressed genes based on  the disease and function (IPA tool) was cellular growth and proliferation with 827 molecules involved. Within this cluster the highest activation was reported to proliferation of cells and cell proliferation of carcinoma cell lines. For the treatment with ovarian cancer enriched medium (CM-SKOV3), the most altered functions were cell death and survival and cell cycle, but in this case they were both reported as decreased. The representative clusters are cell death and M phase. The following top changed function was cellular development including downregulated clusters of differentiations and senescence. Clearly, the inhibition of cellular death, cell cycle, and differentiation indicate the cell quiescence.For the cells treated with fibroblast enriched medium (CM-K21) in the first case study, the top molecular and cellular function detected by cellular growth and proliferation in both C2-ceramide and C2 with PJ34 treated cells and this category was on the second position after cellular movement in C2 variant and cellular development. According to the p value in cells treated with C2 and PJ34 proliferation of tumor cell lines was the first affected function and proliferation of neuronal cells was on the third position. In the C2-ceramide treated cells proliferation of cells was on the second position. It should be emphasized that in both variants proliferation scored very low p value what indicates high data enrichment. On the basis of Z-score its activation was decreased in comparison to control samples. According to activation Z-score in C2-ceramide treated cells the highest decrease was designated for the functions related to the organization of cytoskeleton and cytoplasm; however proliferation of cancer cells was the third decreased function. While increased activation was predicted for the functions as morbidity or mortality and organismal death, apoptosis was the fourth function. In the second experimental variant (C2-ceramide with PJ34) in the top of the relevant decreased functions were those related to cellular movement and development of neurons . However activation of cell survival and proliferation of cells was predicted to be decreased in comparison to control cells. What is more, in this experimental variant necrosis, cell death, and apoptosis were in the top of activated functions.In the second case study IPA analysis revealed significant enrichment in theOn the basis of the above findings, we conclude that the effect of the C2-ceramide enhanced by the PARP inhibition affects the ability of cells to divide and cellular viability as well as genetically controlled reorganization of cellular shape. This intriguing discovery should be subjected to the further analysis.In the last step of the MPH method we selected new markers which characterize cellular subpopulations of our interest. New markers were selected according to the top differences in genes involvement in the functional expression profiles supported by biological knowledge. In the ovarian cancer case study the method revealed the two additional genes characteristic for the cellular quiescence: PI16 and WNT7A. Peptidase inhibitor 16 (PI16) was reported to inhibit cell migration and proliferation and determine cellular quiescence . WNT7A mOn the other hand neuroblastoma cells which entered the cell death pathway are characterized by activation of EGR1, VEGF, and GDF15. While the EGR1 is known to possess proapoptotic properties , VEGF anTop genes characterizing each functional profile determined by the MPH method are listed in In this article, we propose a novel approach to the analysis of transcriptomic data from cellularly homogeneous samples aiming to describe their functional heterogeneity. The main innovation of our idea is based on the assumption that in a population of cells each individual cell conducts its own molecular function. Moreover, each cell in the population may respond in a different way to an external stimuli. These observations resulted in the development of the MPH method that estimates the proportion of cell subpopulations conducting specific cellular functions along with their transcriptomic description.The above description of our results proves that our function characteristic profiles derived from the computational interpretation of transcriptomic data are functionally consistent. We have concluded that they actually correspond to the molecular subpopulations of both ovarian cancer and neuroblastoma cells that were studied.Ovarian Cancer Cell Line. Based on the literature, both healthy fibroblasts (K21) and ovarian cancer cell line (SKOV3) were expected to boost cancer cells proliferation via paracrine manner. We found that conditioned media were sufficient to trigger ovarian cancer cell divisions regardless of serum depletion. Both in vitro experiments and microarray analysis prove that fibroblasts stimulate proliferation extensively, while ovarian cancer secreted factors exert a more subtle effect. This is consistent with the metaprofile results showing that percentage of proliferating cells is significantly higher in the culture with fibroblasts enriched medium. The in vitro experiments support the hypothesis that fibroblasts stimulate proliferation extensively, while ovarian cancer secreted factors exert a more subtle effect. These results are fully consistent with the conclusions based on the output provided by the MPH method. Based on the transcriptomic profiles we identified two cellular activities in the analyzed sample, that is, proliferation and quiescence, while the calculated proportions show that the percentage of proliferating cells is significantly higher in the culture with fibroblasts enriched medium.IPA tool) of the significantly altered genes revealed the activation of cell cycle related genes in the CM-K21 condition. In parallel, in CM-SKOV3 treatment, we observe downregulation of differentiation, proliferation, senescence, and cell death suggesting cell dormancy. Although proliferation was clearly determined in both the first functional profile from the MPH algorithm and the raw transcriptomic data, the opposite process was not automatically defined. None of the commonly used programs  managed to identify dormancy or cell quiescence. However, 8 out of 12 of the most differentiating genes for the second functional profile were linked to quiescence in various studies. The MPH method requires manual analysis, but it allows more profound insight and identification of the nontrivial processes and corresponding markers.The core analysis . The control sample manifests higher proliferation activities and repressed cell death processes. However, our computational analysis suggests that the PARP inhibitor (PJ34) does not increase the cell viability in populations supplied with the C2-ceramide. This fact is not consistent with the results from the MTT assay reported in [orted in .However, since the functional analysis provided in the results section supports our computational results we suppose that the cause for this inconsistence may be the assay used to measure cells viability. The MTT assay depends on concentration and activity of NAD(P)H-dependent cellular enzymes , while PIPA tools. However, in addition it expands our knowledge on the composition of the measured transcriptomic signal by the microarray experiments. We approximate the differences in gene expression levels for cells performing various molecular process and the proportions in which they are mixed.Summarizing, in both case studies the MPH method provides insightful interpretation of transcriptomic data, which is consistent with literature and functional analysis performed by The successful functional validation justifies the applicability of the proposed novel approach to the analysis of transcriptomic data retrieved from homogeneous samples. We illustrate that the methods, used previously at the cellular level to determine the input of each cell-type on the finally observed transcriptome, can be applied to the problem of a subcellular, regulatory nature. The method itself is stable and computationally efficient and provides statistically significant outcome.Finally, it should be noted that methods that engage the nonnegative matrix factorization (NMF) techniques are also applicable in case of RNA-seq data analysis. Various modifications of NMF have been lately used for the inference from the RNA-seq results. For simple detection of the most differentiating genes between experimental and control ones, a method called discriminant NMF (DNMF) was suggested. The DNMF incorporates the Fisher's criterion into NMF by maximizing the distance among any samples from different experimental conditions, meanwhile minimizing the dispersion between any pairs of samples in the same class .DSection method was used by Dozmorov et al. [Additionally, the already presented v et al.  to descrv et al. . NeverthIn this study we presented a novel methodological approach to quantify the functional heterogeneity of a homogeneous cell population based on transcriptomic data. To this aim we adopted the method proposed for quantification of cell proportions in heterogeneous tissue samples  from expression data. Our model framework exploits the methodology designed for RNA expression microarrays applied for heterogeneous tissues. However, it should be emphasized that our novel approach can also be effectively applied to RNA-seq data by adapting the procedures proposed in , 34.The presented case studies were focused on the effect of peritoneal paracrine signaling in ovarian cancer cells and the role of ceramide in mediating cell death in neuroblastoma cells. With the MPH method, in the ovarian cancer study, we identified two cellular activities, that is, proliferation and quiescence mixed in the proportion consistent with the experimental data. Our computational method also quantified the activity of C2-ceramide in time and its influence on cell metabolic activity in a consistent way with the MTT assay. Finally, the method allowed obtaining biologically relevant results describing the biologically meaningful interdependence between C2-ceramide and the PJ34 compound. In this case the specificity of molecular experiment requires the use of additional methods to verify the results of the MTT assay referring to cells viability.DSection and ssKL procedures are characterized by the bias towards discrimination based mainly on fold changes in a given expression dataset. One should note that in the current implementation the ssKL method prevents the use of markers that differ on the direction of expression changes. The appropriate improvement of the decomposition method can constitute a very useful strategy for further research.Here, it should be mentioned that the presented framework could be further improved. Both AppendixC_Influence_of_marker_genes.xlsx: The file contains results for various group of genes to determine such properties as robustness of outcome and its correlation with the fold change.AppendixD_Top_profiles.xlsx: The file contains lists of top 50 genes characterizing all functions from analyzed case studies.


Dynamin is a mechanochemical GTPase essential for membrane fission during clathrin-mediated endocytosis. Dynamin forms helical complexes at the neck of clathrin-coated pits and their structural changes coupled with GTP hydrolysis drive membrane fission. Dynamin and its binding protein amphiphysin cooperatively regulate membrane remodeling during the fission, but its precise mechanism remains elusive. In this study, we analyzed structural changes of dynamin-amphiphysin complexes during the membrane fission using electron microscopy (EM) and high-speed atomic force microscopy (HS-AFM). Interestingly, HS-AFM analyses show that the dynamin-amphiphysin helices are rearranged to form clusters upon GTP hydrolysis and membrane constriction occurs at protein-uncoated regions flanking the clusters. We also show a novel function of amphiphysin in size control of the clusters to enhance biogenesis of endocytic vesicles. Our approaches using combination of EM and HS-AFM clearly demonstrate new mechanistic insights into the dynamics of dynamin-amphiphysin complexes during membrane fission. The nerve cells that make up a nervous system connect at junctions known as synapses. When a nerve impulse reaches the end of the cell, membrane-bound packages called vesicles fuse with the surface membrane and release their contents to the outside. The contents, namely chemicals called neurotransmitters, then travels across the synapse, relaying the signal to the next cell.Nerve cells can fire many times per second. The membrane from fused vesicles must be retrieved from the surface membrane and recycled to make new vesicles, ready to transmit more signals across the synapse. Many proteins at these sites are involved in folding the fused membrane back into the cell, constricting the opening, and eventually pinching off the new vesicles – a process known as endocytosis. Two proteins named dynamin and amphiphysin cooperate in this process, but their precise mechanism remained elusive. Dynamin is a protein that acts like a motor; it breaks down a molecule called GTP to release energy. Previous studies have seen that dynamin-amphiphysin complexes join end to end to form long helical structures.Takeda et al. have now looked at how the structure of the helices changes during endocytosis. This revealed that the dynamin-amphiphysin helices rearrange to form clusters when the GTP is broken down. Further analysis showed that the folded membrane becomes constricted at regions that are not coated with the clusters of dynamin-amphiphysin helices. Takeda et al. also discovered that amphiphysin controls the size of the clusters to help make the new vesicles more uniform.The gene for dynamin is altered in a number of disorders affecting the nervous system and muscles, including epileptic encephalopathy, Charcot-Marie-Tooth disease and congenital myopathy. Moreover, a neurological disorder characterized by muscle stiffness (known as Stiff-person syndrome) occurs when an individual’s immune system mistakenly attacks the amphiphysin protein. As such, these new findings will not only help scientists to better understand the process of endocytosis, but they will also give new insight into a number of human diseases. Clathrin-mediated endocytosis (CME) is the best characterized endocytic pathway by which cells incorporate extracellular molecules into cells as cargoes of clathrin-coated vesicles . CME is 2 . The stalk structure serves as a binding interface for dimerization and oligomerization of dynamin. The BSE, which is located between the stalk and GTPase domain, functions as a flexible hinge required for structural changes of dynamin upon GTP hydrolysis. Dynamin forms helical oligomers which was first observed in presynaptic terminals of shibire mutant flies at restrictive temperature  and high-speed atomic force microscopy (HS-AFM). Firstly, we show that the dynamin-amphiphysin helices are rearranged to form clusters upon GTP hydrolysis, and membrane constriction occurs at protein-uncoated regions between the clusters. Secondly, we reveal that GTP hydrolysis is required and sufficient for the cluster formation by dynamin-amphiphysin complexes by EM analyses. Finally, we show a novel function of amphiphysin in controlling cluster size, which in turn regulates biogenesis of endocytic vesicles. These findings provide new insights into the mechanism of membrane constriction and fission by dynamin-amphiphysin complexes.To elucidate the mechanisms of dynamin-mediated membrane fission, we reconstituted the minimum system in vitro and analyzed the time course of its structural changes using EM. Human dynamin 1 and amphiphysin were purified  and theiNext, we tried to clarify how the membrane constriction and fission by dynamin-amphiphysin helices are correlated with guanine nucleotide conditions during GTP hydrolysis. The appearance of lipid tubules , No GTP Although we determined the requirement of GTP hydrolysis in membrane constriction and fission by the dynamin-amphiphysin complexes, structural changes of the complexes were not clearly resolved in the in vitro assay system using LUVs. To improve the resolution, we used rigid lipid nanotubes containing glycolipid galactosylceramide  , insteadTo correlate the dynamics of dynamin-amphiphysin complexes with GTP hydrolysis, we examined structural changes of the complexes on lipid nanotubes at different transition states of GTP hydrolysis. The appearance of dynamin-amphiphysin helices was unchanged even in the presence of GTPγS or GMP-PNP . FurtherTo elucidate the dynamics of dynamin-amphiphysin helical complexes during the membrane constriction and fission, we analyzed the clustering process of the complexes using HS-AFM . LUVs weWe next tried to correlate the cluster formation of dynamin-amphiphysin helical complexes with membrane constriction and fission. In the representative sample in which membrane constriction and fission occurred, a few dynamin-amphiphysin helices merged to form a cluster over time after GTP addition . InteresWe previously demonstrated that amphiphysin stimulates the GTPase activity of dynamin and thus enhances vesicle biogenesis . In thisIn this study, we analyzed dynamics of dynamin-amphiphysin helical complexes during membrane constriction and fission using EM and HS-AFM. EM analyses showed that GTP hydrolysis is required for both membrane constriction and fission, but dissociation of hydrolytic products (GDP and/or phosphate) seems necessary for the completion of membrane fission . In the There is a consensus view about the requirement of GTP hydrolysis in membrane fission, but the requirement of GTP hydrolysis in membrane constriction is still controversial . MembranIn this study, we revealed that dynamin-amphiphysin helical complexes are rearranged to form their clusters upon GTP hydrolysis  and membIn our previous studies, we showed that amphiphysin enhances dynamin’s GTPase activity in the presence of liposomes . In thisIn conclusion, live imaging analyses using HS-AFM in this study and a study from another group  gave new6 cells/ml and the cells were infected with baculoviruses expressing dynamin1. After cultivation of cells at 28°C for 69 hr, the infected Sf9 cells were harvested by centrifugation at 500 × g for 10 min. The cell pellet was resuspended by 1/20 of the culture volume (30 ml) of HCB (Hepes column buffer)100  and cells were sonicated using a sonicator . The cell lysate was mixed with equal volume of HCB0  to make HCB50  and centrifuged at 210,000 × g for 1 hr at 4°C. Ammonium sulfate was added to the cleared lysate to the 30% saturation and incubated at 4°C for 30 min and centrifuged at 10,000 × g for 10 min to recover the dynamin1 containing fraction in the pellet. The dynamin1 pellet was resuspended with 20 ml of HCB50 and dialyzed against 2L of HCB50 for total 4 hr  using dialysis membrane . The dialyzed dynamin1 fraction was applied to Mono Q5/50 GL column  and bound proteins were eluted stepwise using HCB50, HCB100, HCB250 and HCB1000 buffers. Purified dynamin1 was recovered in HCB250 fraction and purity was determined by SDS-PAGE  with slight modifications. Host bacteria BL21 (DE3) transformed with an expression construct for GST fusions of human amphiphysin (pGEX6P2-HsAMPH) were grown in 1 L of LB medium to the cell density of 0.6–0.8 (OD 600 nm) at 37°C and then protein expression was induced at 18°C for 12 hr in the presence of 0.1 mM IPTG. The bacterial cells were harvested by centrifugation at 7000 × g for 10 min and cell pellet was resuspended by 1/10 culture volume (100 ml) of Elution/Wash 300 buffer . The resuspended cells were sonicated using Advanced-Digital SONIFIER model 250D (Branson) and centrifuged at 261,000 × g for 30 min at 4°C and cleared lysate was recovered in supernatant. To the cleared lysate, 1/100 culture volume (1 ml in bed volume) of Glutathione Sepharose 4B Beads  was added and they are mixed using rotating mixer for 1 hr at 4°C. The beads were washed with the Elution/Wash 300 buffer for 5 times in a repeated cycle of centrifugation at 420 × g for 5 min at 4°C followed by mixing with rotator for 5 min at 4°C. The beads with purified GST fusions of amphiphsyin were equilibrated with PreScission Buffer  and GST-tag was removed by PreScission Protease  by incubating for 12 hr at 4°C. The purified amphiphysin was recovered by centrifuge  using spin column  and purity was determined by SDS-PAGE  and 10% cholesterol (Avanti) were mixed in 250 μl of chloroform in a glass vial . Then chloroform was evaporated using slow-flow nitrogen gas to produce lipid a lipid film on the glass and then completely dried in a vacuum desiccator for 30 min. The dried lipid was rehydrated by water-saturated nitrogen gas followed by addition of 250 μl of filtered 0.3M sucrose for 2 hr at 37°C. The resultant LUVs and lipid nanotubes were passed through 0.4 μm- and 0.2μm- polycarbonate filters respectively 11 times using Avanti Mini extruder. The LUVs and lipid nanotubes  were stored in dark at 4°C avoiding photooxidation.Large unilamellar vesicles (LUVs) and lipid nanotubes were prepared as previously described . For LUVLUVs and lipid nanotubes were diluted to 0.17 mg/ml in cytosolic buffer . Dynamin-amphiphysin complexes (1:1 in molar ratio) were diluted to 2.3 μM in the cytosolic buffer. Formvar filmed EM grids were carbon-coated, then glow-discharged. Droplets of the diluted lipids (10 μl each) were prepared on Parafilm and adsorbed on EM grids for 5 min at room temperature. Then the EM grids with lipids were transferred to other droplets of the diluted dynamin-amphiphysin complexes and incubated for 30 min at room temperature in a humid chamber. To see the temporal effect of GTP hydrolysis, the EM grids were transferred to 1 mM of GTP and incubated for various time periods (from 1 s to 10 min). The reaction was terminated by quick removal of the GTP solution by filter paper at room temperature. Alternatively, the EM grids were incubated either GTP, GTPγS, GMP-PNP, GDP plus Vanadate and GDP to analyze GTP hydrolysis transition state structures. The EM grids were negatively stained with filtered 2% uranyl acetate and observed with transmission electron microscope (HITACHI H-7650).All AFM images shown in this article were capture by a laboratory-built HS-AFM in which the amplitude-modulation mode was used. For the HS-AFM imaging, a small cantilever with dimensions of 7 μm long, 2 μm wide, and 90 nm thick was used (Olympus). Its nominal spring constant and resonant frequency were ~0.2 N/m and ~800 kHz in an aqueous solution, respectively. To obtain a sharp tip, an amorphous carbon pillar was grown on the original bird-beak tip of the cantilever by electron beam deposition (EBD) and then sharpened by a plasma etching in an argon environment. The typical radius of the EBD tip was approximately 2 nm after sharpening. For the amplitude-modulation imaging, the cantilever was oscillated with amplitude less than 10 nm under free oscillation condition and the set-point was set at ~90% of the free oscillation amplitude. For HS-AFM imaging of liposomes and dynamin-amphiphysin complexes with lipid tubules or nanotubes, we used mica covered with carbon film. After coating a freshly cleaved mica surface with carbon film, hydrophilic treatment was carried out by a grow discharge. The liposomes (0.17 mg/ml) were deposited on the hydrophilic mica surface and incubated for 5 min at room temperature followed by deposition of proteins (0.6 μM of dynamin1 and amphiphysin) for 30 min at room temperature. After the incubation, the sample was thoroughly washed by cytosolic buffer to remove excess liposomes and proteins. After the washing, the cantilever tip was approached and the imaging was performed under the buffer.The EM and HS-AFM images were randomly captured to avoid data manipulation and representative images were shown in all the figures. The average pitch between the dynamin-amphiphysin helices in EM images  and HS-A In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been favorably evaluated by Vivek Malhotra (Senior Editor), a Reviewing Editor, and three reviewers. The following individuals involved in review of your submission have agreed to reveal their identity: Aurélien Roux (Reviewer #1) and Simon Scheuring (Reviewer #3).Thank you for submitting your article "Dynamic clustering of dynamin-amphiphysin rings regulates membrane constriction and fission coupled with GTP hydrolysis" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Overall, your findings are of interest, but the reviewers found some aspects of the mechanisms of amphiphysin/dynamin clustering confusing and the fission model also raised contradictory arguments.We invite you to submit a revised manuscript provided you can address the following major points satisfactorily.Major points:1) Explain in better terms how amphiphysin participates in the clustering of dynamin rings. In particular, the reviewers were concerned by the distinction between helices and rings: do dynamin and amphiphysin polymerize as ring, that are then clustered, or is the helical pitch of dynamin helix changed by amphiphysin? Another possibility suggested by the reviewers is that the dynamin helix could be "broken" into rings by amphiphysin, which are then further clustered.2) Regarding your model of fission: It is unclear how your model differs from previously proposed models. The reviewers agree that both the figure and the text should be changed to explain better the role of amphiphysin in clustering of rings/helices of dynamin.3) Some of the authors have shown previously that the stimulatory action of amphiphysin on dynamin is curvature-dependent, and most probably stoichiometry dependent. The reviewers thus ask to clarify what is the stoichiometry of amphiphysin to dynamin (concentration ratios), and to perform similar EM experiment as shown in Reviewer #1:The manuscript by Takeda et al. focuses on the dynamics of dynamin/amphiphysin copolymer upon GTP hydrolysis. The authors use a combination of beautiful electron microscopy techniques and high-speed AFM to show that upon GTP hydrolysis, adjacent rings of dynamin cluster by pairs or more. They also show at the nanometric scale that fission occurs in between those pairs rings. The AFM images show that the pairing is due to dynamic clustering of rings rather than depolymerization/polymerization of rings in another state. Overall, the paper is very convincing and balanced in its arguments. Moreover, it shows how a large structure such as the dynamin helix can dynamically change conformation under the influence of partners and nucleotides. It is also consistent with a recent publication on dynamin, also using high-speed AFM  and showing similar dynamics of the dynamin helix, but with less precision. I thus strongly recommend publication.I however have one experiment to suggest. I guess the authors have used a stoichiometry of 1:1 to generate the dynamin:amphiphysin complex . I was wondering how the results would evolved as a function of the stoichiometry: does increasing amphiphysin's ratio increases clustering dynamics? I think EM data on this would suffice, and this experiment is not essential.Reviewer #2:eLife.The authors have used a combination of high-resolution microscopy, negative staining electron microscopy and high speed AFM to study the organization of amphiphysin and dynamin on membranes. It was previously shown that amphiphysin amplified the enzymatic activity of dynamin and that dynamin-induced scission during endocytosis was perturbed when amphiphysin was deleted. But, the mechanism behind this "boosting" activity is still unclear. Thus, the question is still open. The most interesting result of the paper is the observation of the non-regular helix formed by amphiphysin + dynamin when GTP is present. However, I globally find that this paper is not rigorous enough, with no clear contribution to the understanding of the boosting effect and unjustified conclusions. I thus do not recommend publication of the paper in 1) In their paper, the authors generally describe the arrangement of the proteins on soft or rigid tubes as rings rather than as helices. However, although these proteins form rings in solution (2) The authors observe the reorganization of the helices on rigid lipid nanotubes, as well as on soft tubules, in the presence of GTP or GDP + Vanadate. They describe their observation as a "clustering" of the rings, which is quite misleading. Indeed, the regularity of the protein organization is perturbed, with a non-even distribution of the helices; however clustering again would be more adapted to rings than to helices. Moreover, with dynamin alone, a change of the helix pitch is also observed  and in t3) From HS-AFM, the authors observe the dynamics of tubule constriction. The authors did not discuss the very long time required for this constriction, a few minutes after GTP addition. Moreover, they do not observe fission, which they claim is due to the strong attachment of the tubules to the substrate. They conclude that constriction occurs on the bare membrane near the edge of the dynamin/amphiphysin "cluster", and from that extrapolate that scission would occur at the same place, although not observed here. Moreover, some constriction seems also to occur under the proteins since the height decreases , 227s, b4) The authors show that the size of the vesicles generated by fission of the tubules is smaller when amphiphysin is present as compared with dynamin alone. They suggest that the vesicle size is related to the distance between "ring clusters" on tubules. However, in vivo amphiphysin is involved with dynamin in clathrin-mediated endocytosis, at the neck of spherical buds, and not on tubules. It is thus exaggerating to extrapolate from the observation on the size of vesicles generated in vitro from the scission of tubules, conclusions on the control of vesicle size during clathrin-mediated endocytosis.5) Overall, it is not clear for me what insight is brought by the "clusterase model" to the fission mechanism. In fact, no real mechanism is proposed that explains how amphiphysin facilitates fission, rather a very vague list of possible effects (Discussion) without solid physical basis.Reviewer #3:The paper "Dynamic clustering of dynamin-amphiphysin rings regulates membrane constriction and fission coupled with GTP hydrolysis" presents EM and HS-AFM data of dynamin-amphiphysin complexes on lipid tubules and nanorods providing insights into the constriction/fission mechanism of the proteins.The topic is timely, the data is of highest quality, and the insights of large interest in fields ranging from biophysics to cell biology.There are essentially 4 major findings:1) Dynamin-amphiphysin rings cluster upon GTP hydrolysis.2) Membrane constriction occurs at protein uncoated regions (between clusters).3) GTP hydrolysis is required and sufficient for clustering.4) Amphiphysin controls the cluster size.Altogether, the authors propose a "clusterase" model as the new functional mechanism of action. The authors put the new finding into cellular context  which is very nice.Evidence is presented for all four findings. Some aspects should be strengthened:Clustering: what happens between the clusters? Either the dynamin helix would have a huge pitch  or the helix is broken when clusters form. In this respect "clustering" would be "breakage". I am puzzled why the authors do not comment about this. It might be a most important aspect of their findings that amphiphysin is a dynamin helix breaker.Clustering regulation by amphiphysin: The authors compare +amphiphysin with pure dynamin tubules. Would it be possible to test the hypothesis by addition of low (different) amounts of amphiphysin and analyze by EM cluster size?Figure 6 is missing? As a consequence I am not understanding the proposed fission process.Overstatement:Abstract and Introduction, last paragraph: The use of EM and AFM is in no way "our new approaches" or "a novel approach combining". There are papers since the 90s that combine EM and AFM, and also papers combining EM and HS-AFM .Statistics:The authors give numbers to the 1/10 of the Å , which does not make sense.eLife. Your revised article has been favorably evaluated by Vivek Malhotra (Senior Editor), a Reviewing Editor, and three reviewers.Thank you for resubmitting your work entitled "Dynamic clustering of dynamin-amphiphysin helices regulates membrane constriction and fission coupled with GTP hydrolysis" for further consideration at The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:1) The model does not make much sense in physical terms, and has raised questions from the reviewers (see below). We thus request you to remove the model figure and the text describing the model, as it does not preclude the essential findings of the authors.eLife paper has been published on dynamin-endophilin structure and inhibition , the results of which are consistent with the stoichiometric experiments added by the authors of this manuscript, the reviewers request that you cite this paper and comment it in the discussion part.2) Since a recent Reviewer #1:The authors have fully answered my questions, and have improved the manuscript by providing data with stoichiometric experiments with amphiphysin and dynamin. They clarified the points asked by other reviewers. I thus recommend this paper for publication.Reviewer #2:eLife for endophilin. I think this paper should be cited.I am satisfied with the answers of the authors related to helix versus ring and the new experiments showing that when the relative amphiphysin:dynamin ratio increases, scission is less efficient. This is online with the paper from Hohendahl A, et al. (2017) in eLife.Nevertheless, I still have a serious problem with the last part of the Discussion and the model, which is totally handwaving with no physical consistency. This is only a cartoon that takes up the images of the paper, but without solid mechanism. For instance, on Figure 6C, how is it possible to create torsion in a fluid membrane and why would tension increase? If constriction occurs under the amphiphysin-dynamin ring, why would the tubule radius decrease next to the coat, and not increase, in particular if there is some friction under the coat that tend to perturb lipid diffusion? I don't understand how the friction model from Simunivic et al. (2017) could work here. In the absence of clear physical description that justifies these possible mechanisms, I wonder what is so new in this manuscript and groundbreaking compared to the PNAS paper from Colom et al. that would justify publication in Reviewer #3:The author's responses to the first round of reviewers' comments are careful and additional experiments have been performed. Notably, the experiments with varying dynamin:amphiphysin ratios clarify several questions.eLife in this revised and improved form.The manuscript reads well, and overstatements and vague statements have been removed. In my view the paper provides valuable and novel data showing "Dynamic clustering of dynamin-amphiphysin helices", a timely and important topic, and as such deserves publication in  Major points:1) Explain in better terms how amphiphysin participates in the clustering of dynamin rings. In particular, the reviewers were concerned by the distinction between helices and rings.We thank reviewers for raising this issue and we apologize for misleading terminology. We also think that dynamin or dynamin-amphiphysin complexes form continuous “helices” but not stacks of “rings” on lipid templates. Indeed, we meant with the terms “washer ring” or “ring” for the split washer-like structure that corresponds to one helical turn. To avoid any confusion, we integrated those terms into “helix (helices)” or “helical” for both dynamin- and dynamin/amphiphysin-complexes on lipid templates in the revised manuscript. However, we decided to keep the term “ring” to describe the lipid-free dynamin-amphiphysin complexes in solution, since it sounds more appropriate.Do dynamin and amphiphysin polymerize as ring, that are then clustered, or is the helical pitch of dynamin helix changed by amphiphysin? Another possibility suggested by the reviewers is that the dynamin helix could be "broken" into rings by amphiphysin, which are then further clustered.We think that amphiphysin and dynamin copolymerize to form helices (not rings) in the absence or presence of GTP. Upon GTP hydrolysis, the dynamin-amphiphysin helices form clusters consisting of a few helical turns, and generate protein-uncoated “gap” regions between the clusters. As the reviewer #3 suggested, the helices may be broken at the gap regions, because the clusters are often formed so far apart that the helices are unlikely to stay connected. We added a sentence about the possible helix break in the Discussion  and modified the model  in the revised manuscript.2) Regarding your model of fission: It is unclear how your model differs from previously proposed models. The reviewers agree that both the figure and the text should be changed to explain better the role of amphiphysin in clustering of rings/helices of dynamin.Since dynamin-amphiphysin complexes form smaller clusters compared to those formed by dynamin alone , amphiph3) Some of the authors have shown previously that the stimulatory action of amphiphysin on dynamin is curvature-dependent, and most probably stoichiometry dependent. The reviewers thus ask to clarify what is the stoichiometry of amphiphysin to dynamin (concentration ratios), and to perform similar EM experiment as shown in We thank Aurélien Roux (Reviewer #1) and Simon Schering (Reviewer #3) for suggesting this experiment. In this study, 1:1 ratio of dynamin and amphiphysin  was mixed for all the experiments using the dynamin and amphiphysin complexes. Following reviewers’ suggestions, we examined stoichiometry dependency of dynamin and amphiphysin in the ring complex formation , A, lipoThe ring complex formation and liposome tubulation by dynamin and amphiphysin were not stoichiometry dependent  The model does not make much sense in physical terms, and has raised questions from the reviewers. We thus request you to remove the model figure and the text describing the model, as it does not preclude the essential findings of the authors.The model figure  and its legend has been removed. The text describing the model were removed and/or modified .2) Since a recent eLife paper has been published on dynamin-endophilin structure and inhibition , the results of which are consistent with the stoichiometric experiments added by the authors of this manuscript, the reviewers request that you cite this paper and comment it in the discussion part.eLife paper  has been cited and commented in the Discussion part (fourth paragraph).The recent


During the postpartum visit, health care providers address issues with short- and long-term implications for maternal and child health. Women with Medicaid insurance are less likely to return for a postpartum visit compared with women with private insurance. Behavioral economics acknowledges that people do not make exclusively rational choices, rather immediate gratification, cognitive and psychological biases, and social norms influence decision making. Drawing on insights from decision science, behavioral economists have examined how these biases can be modulated through carefully designed interventions. We have developed a Web-based tool, Healthy Beyond Pregnancy, that incorporates empirically derived concepts of behavioral economics to improve adherence rates to the postpartum visit.The primary objectives of this pilot study were to (1) refine and assess the usability of Healthy Beyond Pregnancy and (2) assess the feasibility of a randomized controlled trial (RCT) of the intervention.We used a multistep process and multidisciplinary team of maternal-fetal medicine physicians, a behavioral economist, and researchers with expertise in behavioral interventions to design Healthy Beyond Pregnancy. We assessed the usability of the program with the Post-Study System Usability Questionnaire (PSSUQ), a validated 7-point scale, and semistructured interviews with postpartum women. We then conducted a feasibility trial to determine the proportion of eligible women who were willing to participate in an RCT of Healthy Beyond Pregnancy and the proportion of women willing to complete the Web-based program. Exploratory outcomes of the pilot trial included attendance at the postpartum visit, uptake of long-acting reversible contraception, and uptake of any contraception.P=.06).The median PSSUQ score for Healthy Beyond Pregnancy was 6.5 (interquartile range: 6.1-7) demonstrating high usability. Semistructured interviews (n=10) provided in-depth comments about users’ experience and further improved the program. A total of 34 postpartum women with Medicaid insurance were approached for the pilot trial, and 30 (88%) were consented and randomized. All women randomized to Healthy Beyond Pregnancy completed the Web-based program, had text-enabled cell phones, and were willing to receive text messages from the study team. Women in the Healthy Beyond Pregnancy arm were more likely to return for a postpartum visit compared with women in the control arm with 85% of women in Healthy Beyond Pregnancy returning versus 53% in the control arm  During the postpartum visit, health care providers address a number of issues with both short- and long-term implications for maternal and child health. Clinicians counsel about contraceptive options, provide breastfeeding support, screen and refer for postpartum mood disorders, screen for cardiometabolic consequences of pregnancy complications, and discuss interconception care. They also connect women with primary care providers.Attendance rates for the postpartum visit are markedly lower for women with limited economic resources . In the The reasons for noncompliance with the postpartum visit are complex . Women sThe field of behavioral economics acknowledges that people do not make exclusively rational choices. Immediate gratification, cognitive and psychological biases such as bounded rationality or status quo bias, and social norms profoundly influence decision making. Drawing on insights from psychology and decision science, the field of behavioral economics has examined how these biases can be modulated through carefully designed interventions . IncreasWe used a multistep process and multidisciplinary team of maternal-fetal medicine physicians, a behavioral economist, certified lactation consultant, and researchers with expertise in behavioral interventions to design Healthy Beyond Pregnancy. The broad conceptual steps that we used to develop and test Healthy Beyond Pregnancy are illustrated in First, bounded rationality and information overload indicates that patients’ decision making is hampered by the overwhelming amount of information available and the difficulty in focusing on all of the information relevant to their care. Furthermore, the perception of personal relevance of the information presented will affect how the information resonates with the patient and how motivating it is toward healthy behavior. Given this, Healthy Beyond Pregnancy allows participants to define much of the content of their postpartum education and acknowledges that only 2 to 3 issues can be meaningfully addressed for most patients. The first step on the Healthy Beyond Pregnancy Web platform is a survey that assesses the participants’ postpartum concerns from a scale of 1 to 5—with 1 representing not at all important to 5 representing very important. Women are presented with the following list of postpartum issues: (1) postpartum contraception, (2) breastfeeding support, (3) postpartum mood, (4) bowel and bladder function after delivery, (5) sexual activity after delivery, (6) optimizing interpregnancy health, and (7) follow-up after pregnancy complications such as gestational diabetes, hypertension, or spontaneous preterm delivery. Women’s answers on the scale of 1 to 5 are entered into an automated algorithm, and they watch 2 to 4 videos that reflect their self-identified needs—women watch the videos that they scored as most important . Women with a pregnancy complicated by gestational diabetes, hypertension, or preterm birth will also view videos about the implications of these pregnancy complications. Given the health benefits of planned and timed pregnancies as well as breastfeeding, if a participant indicates that she is not interested in any of the postpartum domains, she will be shown videos on contraception and breastfeeding. Women are given the option to watch more videos if they want.Second, status quo bias/or lack of self-control indicates that patients often make time-inconsistent choices—they may plan to go for a postpartum visit but put off making the appointment because the immediate costs  loom larger than the delayed benefits of the visit . HealthyThird, hovering or limited attention indicates that several tasks and choices compete for patients’ attention. Patients need reminders to keep an action on the top of their mental stack . Thus, HFourth, the framed incentives emphasize on the fact that the uptake of behaviors can be influenced by salient incentives with proper framing . HealthyWe recruited a convenience sample of 15 women from the postpartum floors of Magee-Womens Hospital. Participants were recruited in three groups of 5 with iterative improvements made to the website after each group of 5 completed their assessments. All participants used the website and completed a usability measure. A subset of women also participated in a semistructured interview. Women were interviewed until thematic saturation was reached, which occurred after interviewing 10 women.After viewing the Healthy Beyond Pregnancy program, participants completed a printed questionnaire to assess the website’s usability. Usability is defined as the extent to which a product can be used to achieve its stated goals with effectiveness, efficiency, and the satisfaction of the user . We admiAfter viewing the Healthy Beyond Pregnancy site, 10 participants also completed a semistructured interview. In the interviews, participants were asked about the strengths and weaknesses of the program, as well as recommendations for improvement. Interviews were audiotaped and transcribed for analysis. No field notes were taken, and transcripts were not returned to the participants. Interview questions are included see .For the PSSUQ, medians and interquartile ranges (IQRs) were calculated. A nonparametric test of trend (nptrend) was performed to compare scores across the three groups of 5. Analyses were completed using STATA 13 (StataCorp LLC).To create the initial coding scheme, two investigators independently performed coding of two interviews to identify themes. The coding scheme was collaboratively modified after application of initial codes to two additional interviews. All interviews were then thematically recoded with the final coding scheme. We continued interviews until thematic saturation was reached (n=10). Qualitative coding was organized using ATLAS.ti 4.2.We conducted a pilot RCT to test the feasibility of randomizing postpartum women to Healthy Beyond Pregnancy or usual care. The trial was conducted at Magee-Womens Hospital, a large maternity hospital that provides care to women in Western Pennsylvania. The institutional review board of the University of Pittsburgh approved the trial (PRO16090292).Inclusion criteria for the trial were (1) postpartum 6 to 72 hours from their delivery, (2) aged 18 to 50 years, (3) receipt of prenatal care through the Magee-Womens Hospital outpatient obstetrical clinic, and (4) “UPMC for You” Medicaid insurance. Women were excluded if they delivered in less than 24 weeks, experienced a fetal or neonatal death, did not speak English, or did not have a text-enabled phone. We recruited for the trial from November 2016 to February 2017.Study investigators (KPH and FLF) who were part of the clinical team identified women eligible for the study. Participants were then approached for the study, consented, and randomized on the postpartum floor. We used computer-generated randomization to assign participants to Healthy Beyond Pregnancy or usual care in a 1:1 ratio. The Healthy Beyond Pregnancy program is described in detail in phase 1. It is not embedded in other parts of the hospital care and was administered by the members of the study team. The control arm received routine clinical care. This includes a reminder in their discharge paper work to call their clinic for a postpartum visit in 3 to 8 weeks.Our primary outcome included the proportion of eligible patients who consented to the study and the number of women randomized to Healthy Beyond Pregnancy who completed the Web-based program. We also assessed whether patients would recommend the program to a friend.Exploratory outcomes included the proportion of women who attended a postpartum visit within 21 to 56 days after delivery and had an uptake of long-acting reversible contraception (LARC) and some form of contraception. The 21- to 56-day period is consistent with the Healthcare Effectiveness Data and Information Set (HEDIS) definition of a postpartum visit.Maternal and clinical data were abstracted from the medical records. These included maternal age, race, parity, gestational age at delivery, mode of delivery, opiate use during pregnancy, and number of prenatal visits.t test or chi-square test. Differences in exploratory outcomes—attendance at the postpartum visit, receipt of LARC, or receipt of any birth control method other than condoms—between study arms were compared using univariate logistic regression. Importantly, this study was not powered to detect differences between groups in exploratory clinical outcomes such as adherence to the postpartum visit, and given the small sample size, multivariable modeling was not performed.Outcomes were described using means or proportions. Demographic and clinical characteristics were compared between study arms using either independent sample A total of 15 women (three groups of 5 based on the timing of enrollment) participated in usability assessment of the Healthy Beyond Pregnancy website. Iterative improvements were made after each group of 5 completed their assessments. Participants were postpartum women aged between 22 and 38 years. Users spent between 9 to 15 min completing the program.P=.52).The median PSSUQ score was 6.5 (IQR: 6.1-7) demonstrating high usability. Each of the subscales also demonstrated high usability scores—median score on system quality was 6.6 (IQR: 6.25-7), median score on information quality was 6.6 (IQR: 5.8-7), and the median score on interface quality was 7 (IQR: 6-7). Although the median overall PSSUQ score improved over the course of the three usability testing groups—Group 1: 6.5 (6.5-7), Group 2: 6.7 (6.5-7), and Group 3: 6.8 (6.5-7)—this was not significant (The semistructured interviews (n=10) provided more in-depth comments about users’ experience of using Healthy Beyond Pregnancy. The interview questions are provided in The median interview time was 14 min (IQR: 10-15). Overall comments were positive with 90% (n=9) of women indicating that they would recommend the program to a friend who had just delivered. Important design improvements also emerged from these interviews. For example, we restructured our scheduling calendar to make available appointments easier to identify, changed the language in the tablet computer to make it more accessible (preterm birth became delivery in less than 37 weeks), and added a written summary of the personalized information provided by Healthy Beyond Pregnancy. A total of 34 women were approached for the pilot trial, and 30 (88%) were consented and randomized . ImportaP=.06). Importantly these results were not significant. All exploratory outcomes are outlined in All participants enrolled in the trial had UPMC Medicaid insurance, and thus, we were able to ascertain our clinical outcomes on all patients, as they must seek care through a UPMC facility, all of which use a common electronic medical record system. There was a trend toward more women in the Healthy Beyond Pregnancy arm returning for a postpartum visit compared with women in the control arm, that is, 85% of women in Healthy Beyond Pregnancy returning versus 53% in the control arm—odds ratio of 5.3  and 7% (n=1) of our control group and Healthy Beyond Pregnancy group, respectively. As there are benefits beyond contraception to the postpartum visit, we opted not to exclude these women from the trial. Furthermore, at our institution, some women with UPMC for You insurance qualify for an etonogestrel implant (a LARC method) before discharge. This, however, is not true for other Medicaid insurance products. Finally, women can also opt to get a single medroxyprogesterone injection or a prescription for 3- to 6-month supply of combined oral contraceptive pills before discharge from the hospital. In addition, 20% (n=3) of women in our control arm fall into this category. Although there is documentation of contraception provision for these women, without establishing postpartum care, these women are at risk of not being able to establish a long-term contraception plan. Further investigation of our study tool with a larger sample size and a longer follow-up period is needed to help understand the impact of Healthy Beyond Pregnancy on contraception use after delivery.The willingness of Medicaid recipients to participate in a trial designed to improve compliance with the postpartum visit is important because attendance rates for the postpartum visit are lower for women with limited resources, potentially contributing to health disparities. Minority women and women of lower socioeconomic status are at significantly increased risk of unintended pregnancies, short interpregnancy interval, and short duration of breastfeeding. The maternal and child health outcomes related to unintended pregnancies, short interpregnancy interval, and short duration of breastfeeding are well documented, and importantly, these measures can be impacted during the postpartum period -31. FurtAn important component of our intervention is that it is designed to be both affordable and scalable. There are a number of other postnatal interventions, including patient education booklets, home visits, prescheduling visits, and cash incentives, that have been designed to improve postpartum care in the developed world ,9,32-35.It is important to emphasize that this was a usability study and pilot RCT to assess the feasibility of enrolling patients in a large study of Healthy Beyond Pregnancy. We enrolled patients immediately postpartum. This is a busy and potentially emotionally charged time for women. Furthermore, our intervention targets women from disadvantaged socioeconomic backgrounds who have additional stressors in the immediate postpartum period. Before pursuing a large RCT, we wanted to assess our ability to consent, randomize, and retain women in our study. Given the pilot nature of the project and small sample size, our findings regarding adherence to the postpartum visit must be viewed with caution. It is also important to note that our Healthy Beyond Pregnancy arm had significantly more nulliparous women than our control arm. Women with multiple children may be less likely to attend a postpartum visit. Thus, the greater proportion of nulliparous women in the Healthy Beyond Pregnancy arm may contribute to our increased adherence to the postpartum visit in this group. Nevertheless, the information garnered from this pilot trial will be important for a future efficacy trial. A larger trial will allow us to look definitively at attendance at the postpartum visit, as well as important health outcomes such as breastfeeding duration and provisions of LARC. These outcomes are critical to improve a number of short- and long-term maternal and child health outcomes.We have developed a usable and acceptable Web-based program designed to increase attendance at the postpartum visit. Our pilot trial demonstrates that women are willing and able to participate in a randomized trial of a Web-based program and text messaging system. Importantly, although our trial was not powered to detect difference in attendance at the postpartum visit, we observed a trend toward increased compliance with the postpartum visit among women randomized to Healthy Beyond Pregnancy. A large RCT is needed to determine whether attendance can be increased robustly and whether this would translate into improved health outcomes.


Gestational diabetes mellitus (GDM) is a state of glucose intolerance with onset during pregnancy. GDM carries prenatal and perinatal risks as well as long-term risks for the mother and her child. GDM may be involved in the foetal programming of long-term cardiovascular health. However, evidence is sparse and the effect of GDM on cardiovascular health is unknown. To address these issues, we will conduct MySweetHeart Cohort study. The objectives are to assess the effect of GDM on offspring’s cardiovascular health early in life by using surrogate markers of cardiovascular disease and atherosclerosis.This is a cohort study of 100 offspring of women with GDM and 100 offspring of women without GDM. At inclusion, a baseline assessment of the mothers will be conducted through means of self-report questionnaires, a researcher-administrated interview, blood pressure and anthropometric measurements, and a maternal blood sampling. Between the 30th and 34th weeks of gestation, a foetal echography will be performed to assess the foetal cardiac structure and function, the fetomaternal circulation and the hepatic volume. At birth, maternal and neonatal characteristics will be assessed. An echocardiography will be performed to assess cardiac structure and function 2–7 days after birth; carotid intima-media thickness will be also measured to assess vascular structure. MySweetHeart Cohort is linked to MySweetHeart Trial , a randomised controlled trial assessing the effect of a multidimensional interdisciplinary lifestyle and psychosocial intervention to improve the cardiometabolic and mental health of women with GDM and their offspring. A long-term follow-up of children is planned.Ethical approval has been obtained through the state Human Research Ethics Committee of the Canton de Vaud (study number 2016–00745). We aim to disseminate the findings through regional, national and international conferences and through peer-reviewed journals.NCT02872974).ClinicalTrials.gov (clinicaltrials.gov/ct2/show/ This study will increase our understanding of the impact of gestational diabetes mellitus on cardiometabolic health during foetal and neonatal periods. Within a Developmental Origin of Health and Disease framework, it will contribute to improving the knowledge on the early life conditioning (programming) mechanisms and their influence on infants’ cardiovascular health.A major strength of our study is the assessment at birth of surrogate markers of cardiovascular disease (CVD) ).Acknowledged limitations are the relatively small sample size, the potential for residual confounding and the limited representativeness of our sample (monocentric study).A better understanding of the clinical impact of the maternal hyperglycaemic disorders on offspring’s health early in life is needed to inform strategies for the early prevention of CVD.A long-term follow-up of children is planned for further assessment of their cardiovascular health.The prevalence of maternal hyperglycaemic disorders during pregnancy is increasing in the population due to the obesity epidemic and the increasing age of pregnant mothers.2Maternal T1/T2DM diabetes is associated with significant fetal and neonatal morbidity,4 12–15Following the results of these studies, the International Association of Diabetes and Pregnancy Study Groups (IADPSG) have proposed new criteria to diagnose GDM.3Maternal hyperglycaemic disorders are associated with fetal cardiac and vascular structural and functional alterations. For instance, it is well known that offspring of T1/T2DM mothers are at increased risk of congenital cardiac malformations and cardiac hypertrophy.23Intrauterine exposure to high maternal blood glucose is associated with foetal hyperinsulinism which is responsible for structural and functional changes affecting mostly the liver and the cardiovascular system. The liver is the major metabolic organ, considered as the metabolic brain and responsible for the distribution of the placental resources.Most studies on the effect of maternal hyperglycaemic disorders were conducted among mothers with T1/T2DM, not among mothers with GDM and with an emphasis on the effects on offspring’s metabolic outcomes rather than on offspring’s cardiovascular health. It is also unknown whether treatment of GDM is effective to reduce long-term risk of offspring’s metabolic and cardiovascular disease (CVD) riskOur objectives are to assess the effect of GDM on offspring’s cardiovascular health early in life, namely on (1) the surrogate markers of CVD and atherosclerosis at birth (LVMI and cIMT) (primary outcomes) and (2) the cardiovascular structure and function during the foetal period and potential neonatal cardiovascular risk factors (secondary outcomes).We plan to conduct a cohort study of 200 offspring of women aged 18 years old or more. We will include 100 women with GDM and 100 without GDM. All pregnant women attending the antenatal care clinic or the GDM clinic at the Lausanne University Hospital (CHUV) will be invited to participate. In addition, women with GDM who are followed up by private diabetologists and gynaecologists in the Canton de Vaud will be invited to participate following a similar procedure. Using the new criteria of the IADPSG, the expected prevalence of GDM in this population is at least ~10%.Inclusion criteria: Pregnant women aged 18 years or older, with or without GDM at 24–32 weeks of gestation, and understanding French or English. Exclusion criteria: Women on strict bed rest, with pre-existing DM or severe mental disorders precluding participation.Primary outcomes are surrogate markers of CVD and atherosclerosis at birth, that is, LVMI and cIMT. Secondary outcomes are foetal cardiovascular structure and function (notably LVMI and liver volume) and potential neonatal cardiovascular risk factors , etc).During pregnancy, in the pre-recruitment phase, all pregnant women without pre-existing DM, attending the CHUV antenatal care clinic, have a fasting blood glucose measurement between the 24th and 28th weeks of gestation. GDM is diagnosed if fasting blood glucose is equal to or above 5.1 mmol/L. If fasting blood glucose is equal to or above 4.4 and below 5.1 mmol/L, pregnant women have a 2-hour 75 g OGTT and GDM will be diagnosed based on the new criteria of the IADPSG.The participation in the study is voluntary and involves a sequence of events and measurements as summarised in At the first study visit (V1), scheduled between the 24th and 32nd weeks of gestation, a baseline assessment of the mothers will be conducted through means of self-report questionnaires and a researcher-administrated interview, weight, height and blood pressure measurements, and a maternal blood sampling. This will provide information notably on the socioeconomic status, general health status, family medical history of CVD or diabetes, smoking and drinking habits and several cardiometabolic biomarkers, all of which will be treated as potential confounding factors. If available, paternal data on the family history of CVD or diabetes will be also collected at the first study visit.At the second visit (V2), between the 30th and 34th weeks of gestation, a foetal echography will be performed to assess the fetal cardiac structure (including LVMI) and function, the fetomaternal circulation, and the hepatic volume.In women with GDM, information about treatment and blood glucose measurements will be recorded during the whole pregnancy.At birth (V3), maternal characteristics  and neonatal characteristics  will be assessed. A sample of umbilical cord blood will be collected to measure various biomarkers, including glucose, insulin, total cholesterol, low-density lipoprotein (LDL)-cholesterol, high-density lipoprotein (HDL)-cholesterol, triglycerides, uric acid, creatinine, hs-CRP and various miRNA.An echocardiography will be done to assess cardiac structure (including LVMI) and function 2–7 days after birth (V4). cIMT will be measured to assess vascular structure.Maternal body weight and blood pressure , blinded to the maternal glycaemic status, using a Voluson E10  equipped with a 2–8 MHz convex array sector transducer.This examination will be performed 2–7 days after birth (before the mother and the newborn leave the clinic) by two experienced ultrasonographers  blinded to the maternal glycaemic status and to the foetal echocardiogram. Echocardiography will be performed on a Philips EPIC echocardiogram with a S8-3 or S12 MHz transducer, digitally recorded  and analysed off-line. Standard echocardiography including 2D, M-mode, colour and spectral Doppler according to the American Society of Echocardiograph (ASE) will be performed.54–56This examination will be performed 2–7 days after birth (before the mother and the newborn leave the clinic) by two experimented ultrasonographers  blinded to the maternal glycaemic status. Carotid IMT measurement will be performed on a Philips EPIC echocardiograph  with a L 11–5 MHz high-resolution linear array transducer, recorded on a digital system . Image acquisition will be done according to the standard of the American Heart Association Atherosclerosis, Hypertension and Obesity in Youth Committee of the Council on CVD in the Young.59Recruitment has begun in September 2016. About 3200 deliveries per year occur at our hospital and about 250 pregnant women are followed for GDM at our specialised clinic. A relatively large share of patients consists of immigrants who do not speak English or French and will not be eligible for participation. We therefore expect to include up to two pregnant women per week, hence to include the 200 subjects in 30 months. A research coordinator (SE) and a PhD student (AME) will be responsible to screen all women for eligibility and to ensure follow-up throughout the study duration. Recruitment will be facilitated by the high support of obstetricians at the CHUV. We will also benefit of the new specialised GDM clinic of the CHUV where every pregnant woman who screened positive for GDM at the CHUV antenatal care clinic is followed up. MySweetHeart Cohort is linked to MySweetHeart Trial , a randomised controlled trial led by this new specialised GDM clinic designed to assess the effect of a multidimensional interdisciplinary lifestyle and psychosocial intervention to improve the cardiometabolic and mental health of women with GDM and their offspring. Little loss to follow-up is expected because measurements are made during pregnancy and shortly after delivery. Nevertheless, to minimise loss to follow-up, most appointments are made on the days of regular follow-up visits and the postnatal echocardiography is scheduled before the mother and the baby leave the hospital.2.7(SD: 4.5) in children of mothers without GDM2.7(SD: 4.5) in children of women with GDM, the required sample size is 80 women with GDM and 80 women without GDM to have a statistical significant difference with a power of 80% and an alpha-level set at 0.05 (two sided). This sample size is also sufficient to observe statistical significant differences in cIMT at birth if we assume that cIMT at birth is 0.44 mm (SD: 0.04Assuming that LVMI will be 30 g/mThe association between exposure (GDM/no GDM) and the (continuous) outcomes will be estimated with linear regression analyses. Adjustment for potential confounding factors  will be done. To assess the direct and indirect (through mediators) effects of GDM on the outcomes, causal mediation analyses will be conducted.The study poses little to no risk to participants and their offspring. Signed informed consent is obtained from all participating women. Participation in the study does not interfere with the typical care patients receive during pregnancy and after delivery. Clinicians in the obstetrical clinic provide clinical follow-up and, if necessary, participants are referred on for additional clinical management.Results from this study will be disseminated at regional and international conferences and in peer-reviewed journals.The current high prevalence of maternal obesity and associated hyperglycaemic disorders may lead to a perpetuating intergenerational cycle of increasing obesity, metabolic and cardiovascular disorders. Well-designed prospective studies are necessary to better quantify the actual impact of maternal hyperglycaemic disorders on offspring’s health and to identify the potential underlying mechanisms. Despite recent significant advances in DOHaD and foetal programming research, major challenges have to be addressed, notably by better objectively characterising both early life exposure and cardiometabolic outcomes.23Indeed, many past studies on the foetal programming of cardiometabolic disorders suffered from some methodological flaws including confounding, no or poor standardisation of exposure and outcome assessment, and selection bias. Our prospective population-based study in pregnant women whose offspring is examined during fetal life and at birth avoids some of these issues. The long period needed for CVD to develop could be a limitation, but this will be overcome in our study by measuring surrogate outcomes (including LVMI and cIMT) that are well-established precursors of CVD.By looking at the fetomaternal circulation, foetal cardiovascular system and liver and foetal growth and CVD risk markers at birth, we will acquire unique data to gain insight in the early mechanisms underlying the development of CVD and metabolic diseases and on the role of maternal hyperglycaemic disorders. GDM is an opportunity for timely intervention for the prevention of cardiometabolic disorders in mothers and their offspring.