Drosophila embryo surface, smooth interfaces form between expanding Arp2/3-based actin caps and surrounding actomyosin networks, demarcating the circumferences of nascent dome-like compartments used for pseudocleavage. We found that forming a smooth and circular boundary of the surrounding actomyosin domain requires Arp2/3 in vivo. To dissect the physical basis of this requirement, we reconstituted the interacting networks using node-based models. In simulations of actomyosin networks with local clearances in place of Arp2/3 domains, rough boundaries persisted when myosin contractility was low. With addition of expanding Arp2/3 network domains, myosin domain boundaries failed to smoothen, but accumulated myosin nodes and tension. After incorporating actomyosin mechanosensitivity, Arp2/3 network growth locally induced a surrounding contractile actomyosin ring that smoothened the interface between the cytoskeletal domains, an effect also evident in vivo. In this way, a smooth structure can emerge from the lateral interaction of irregular active materials.Structures and machines require smoothening of raw materials. Self-organized smoothening guides cell and tissue morphogenesis and is relevant to advanced manufacturing. Across the syncytial  Smooth components are integral to the assembly and function of human-made structures and devices. Smooth surfaces dominate our inside and urban environments and are formed by refinement of rough starting materials. In conventional industries, starting materials are smoothened by tools. Smooth structures also convey important functions in living systems, but their formation relies on self-assembly and self-organization. Fuller understanding of these mechanisms will aid advanced manufacturing with smart materials for a broad range of applications; from sensors and data processing, to filters and self-cleaning surfaces, to medical devices and robotics .Drosophila wing imaginal disc, gene expression patterns define the cells of specific compartments, but non-muscle myosin II (myosin hereafter) is then required to pull actin networks into straight cables integrated via cell-cell junctions to form smooth compartment boundaries that define the architecture of the mature wing , the broad ring maintained its structure . With fuDrosophila embryo cleavage have shown that Arp2/3 is required for displacing actomyosin networks from the cap and that myosin activity is needed for restraining lateral cap growth. These and other data suggest that the two networks physically engage to control each other’s distributions  with two different myosin node densities (0.1 and 0.2). Compared with the myosin network boundaries formed in the absence of Arp2/3 networks , local sAlthough proper syncytial structure requires regulators that reduce cortical actomyosin activity , our in To incorporate mechanosensitive elevation of local myosin node activity into the simulation, the activity of a myosin node was increased 6-fold if it was displaced to a pixel already occupied by five or more myosin nodes (see Model Formulation). This approach did not explicitly link myosin node modification to the Arp2/3 networks, as the displacement of a myosin node for any reason could induce the activity elevation. However, comparison of myosin node activity elevation events with and without Arp2/3 networks revealed that the elevations occurred predominantly at interfaces between the actomyosin and Arp2/3 networks , arrows,To test how local, Arp2/3-dependent, myosin node activity elevations affected the interface between the actomyosin and Arp2/3 networks, we compared simulations with and without the activations. Strikingly, the elevations significantly enhanced the smoothness and circularity of the interfaces , compareSince smoothening and circularization of the interface coincided with local enrichment of myosin nodes activated by the pushing forces of centrifugal Arp2/3 network growth, we hypothesized that re-shaping of the interface occurred through formation and contraction of an actomyosin ring within an otherwise weakly contractile actomyosin network. To test this idea, we first examined the behavior of an isolated single ring of myosin nodes with uniform activity equal to the activity induced by Arp2/3 network growth in the two-network simulations. The isolated network was initiated as a thick, rough-edged ring of randomly positioned myosin nodes containing a central clearance instead of an Arp2/3 network  with equal myosin activities (M1 and M2), pulling between n1 and n2 would displace both nodes by the same distance toward each other. The force experienced by each node is defined by 1 and n2, and the coefficient Kmyosin assigns units of force to the myosin activity . Each node is visualized as a single pixel. However, node connection angles, node connection distances, force angles, and node displacements are defined at 1/100th of a pixel. Since the cell cortex is 50–400 nm thick , the posAfter the myosin nodes are positioned across 2D space they are linked by permanent connections. Each node is randomly connected with a maximum of six other nodes within a search radius of 5 pixels (500 nm). This design is based on myosin mini-filaments (i) having 28–58 motor domains , which wth’ myosin node are determined by:Once an interconnected array of nodes is assembled, myosin activity is triggered to simulate network contraction. The pulling forces from ‘n’ connected neighboring myosin nodes on the ‘mth’ node.myosin: Coefficient of myosin force.Km: Myosin node activity level of the ‘mth’ node.Mi: Myosin node activity level of the ‘ith’ connected node.Mth node from the mth node.th’ myosin node are determined by:In addition, cross-linked actin networks display elastic responses to stretching but not compression . This asth’ node.spring: Coefficient of spring force li-lo: Current length of connection – resting length of connection lo: Mean length of all connections before a simulation starts.Kth node from the mth node.−1 .ξ: Damping coefficient.th’ myosin node, its new position is calculated after every simulation step by:Using the pre-existing position and the net displacement of the ‘mDrosophila . Annotated codes are provided . MATLAB and Image J (NIH) were used for quantifications. Excel (Microsoft) was used for graphing means ± SD, and for determining p values with T-tests of samples with unequal variance and two-tailed distributions. PowerPoint (Microsoft) was used for schematics. Photoshop (Adobe) was used for figure preparation.To quantify the area of growing Arp 2/3 networks with and without a wall , the outTo quantify inner clearance areas in single ring simulations , a custoS, of the entire boundary of the central clearance was calculated as the inverse of the mean of the standard deviations, σ, over the six segments, as follows:For quantifications of interface properties in the multi-ring simulations , the bouS close to ~nine from MATLAB-generated circular plots.The calculated smoothness approaches infinity for perfectly smooth shapes, but the pixelated images generated by MATLAB are not perfectly smooth, and we calculated 2O to 1000 ml) plates at 25°C after 2–3 days of caged adult feeding on dabs of store-bought baker’s yeast with daily plate changes. Adults were caged for embryo collection within 1 week of pupal hatching, and no health issues were noticed. Embryo sexes were not determined and embryo populations with a specific genotype of interest displayed relatively normally distributed phenotypes suggesting no detectable sex contribution.Animals were maintained under standard conditions. True breeding stocks were maintained at room temperature, 18°C or 25°C on fly food provided by a central University of Toronto kitchen operated by H. Lipshitz. Embryos were collected on plates of apple juice agar , plus dHDrosophila Stock Center (BDSC) #53972) and control RNAi  were expressed maternally using maternal-GAL4-VP16 (gift of Mark Peifer) and myosin localization was assessed in offspring using a GFP insertion into the zipper (zip) gene locus . Standard Drosophila genetics synthesized the maternal genotypes used: maternal-GAL4-VP16 /+; Zip-GFP Trap/UASp-Arp3-shRNA and maternal-GAL4-VP16 /+; Zip-GFP Trap/+; UASp-mCh-shRNA/+.UAS constructs for Arp3 RNAi . The coverslip, with the embryos facing up, was set into the bottom of a glass bottom culture dish with its original coverslip removed. Images were collected with a spinning-disk confocal system (Quorum Technologies Inc) at RT with a 63x Plan Apochromat NA 1.4 objective , a piezo top plate, an EM CCD camera (Hamamatsu Photonics), and Volocity software (Quorum Technologies Inc). Z stacks had 300 nm step sizes. Images were analyzed with Volocity software and ImageJ (NIH). In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:This manuscript presents computer simulations that demonstrate how smooth boundaries can be created between a zone of active expansion and a second zone of active constriction that surrounds it. This work is of interest to scientists working in the field of cytoskeletal organization, mechanobiology, and self-organizing active matter.Decision letter after peer review:eLife. Your article has been reviewed by 2 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Anna Akhmanova as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "Emergence of a smooth interface from growth of a dendritic network against a mechanosensitive contractile material" 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) Provide a physical (or mechanistic) explanation for the observed smoothening behavior.2) Test how sensitive the main results are to initial conditions, and to different parameter values by performing a sensitivity analysis .3) Describe the model a bit more specifically at the beginning of the result section so the reader has a general sense of how it was implemented.4) Using physically relevant units in the text and the table would make it easier to follow and potentially more impactful. Or the authors should explain if there is a good reason to keep those non-physical units.5) Please provide Matlab files at resubmission.Reviewer #1:Drosophila embryo during pseudo-cleavage. This is an interesting question in the context of how actin networks are organized. To understand interface smoothing, the authors perform "node-based" simulations of the two actin networks. The simulation methods of the two networks follows previously published methods and are validated through comparisons with previous work. For the interface between these networks, the authors invoke some ad hoc rules that are poorly justified form a physical point of view. It is not clear, how much their results depend on this choice of interfacial dynamics. Whereas the simulation results are quantitatively analyzed, there is essentially no quantification of the experiments, and the comparison between experiment and theory remains qualitative. Eventually, the authors propose a set of ingredients that are sufficient to yield smooth interfaces in their simulations. However, a thorough understanding in terms of the physical mechanism underlying the simulation results remains elusive. For these reasons, in its current state, this works seems of limited use for the community.The authors attempt to understand the basis of smoothing interfaces between Arp2/3-based actin networks and actomyosin networks in the syncytial Reviewer #2:In this manuscript, Sharma et al., aim to better understand the mechanical mechanisms underlying the organization of the syncytium, the cortical meshworks of actin and myosin under the surface of the fly embryo during early embryo development. This meshwork is composed of two networks that self-organize into circular caps containing branched actin filaments and surrounded by an acto-myosin constrictive network. Using a model based on nodes that follow simple mechanical rules, the authors demonstrate that one can start with roughly defined zones where each meshwork is defined, and only in certain conditions these zones will become clearly defined with a smooth border as seen in the fly embryo. They show that clear and smooth boundaries appear only when a branched actin meshwork expands in the caps and when there the surrounding acto-myosin network exerts enough contractile forces especially at the interface between both meshworks.Strengths:The modeling of the actin and myosin meshworks is performed using phenomelogical rules at a meso-scale, which allow the authors to focus on general mechanical properties of the meshworks and limit the number of free parameters.The authors nicely demonstrate what mechanisms cannot lead to smooth boundaries and which one can.The authors systematically compare their simulations with experimental data in wild-type and in knock-down flies that have been published before or that they generate for this study.Weaknesses:The parameters are discussed in the text in arbitrary non-physical units . It is sometimes difficult to follow whether the values used are realistic or not. That said the parameter table gives some equivalence but this prevents a smooth read.Some of the parameters used in all the simulations are set to certain values but those values are often not discussed, and it is unclear to which extent the results of the simulations are sensitive to those parameters.The code is provided only as a pdf file which prevents the reader to run the simulations themselves.The authors could test how sensitive their main results are to initial conditions, and to different parameter values by performing a sensitivity analysis .Please provide Matlab files at resubmission.Things that could be clarified:The authors could explain a bit more how the initial rough patterns of Arp2/3 and acto-myosin zones are generated in the embryo. Is it signaling? Could it be self-organized from a random initial organization by the mechanics too?They could describe the model a bit more specifically at the beginning of the result section so the reader has a general sense of how it was implemented.Using physically relevant units in the text and the table would make it easier to follow and potentially more impactful. Or the authors should explain if there is a good reason to keep those non-physical units. Essential revisions:1) Provide a physical (or mechanistic) explanation for the observed smoothening behavior.It was important to flesh out the mechanism involved. Our first submission showed that centrifugal expansion of a rough Arp2/3 network against a surrounding and rough actomyosin network is insufficient for forming a smooth interface between them, but that Arp2/3 growth did displace myosin nodes and increase strain between them. Based on mechanosensitive strengthening of actomyosin networks reported in the literature, we allowed myosin nodes to increase their activity with a specific degree of displacement. As a result, myosin nodes gained activity in a ring around the interface of the Arp2/3 network and the surrounding actomyosin network, specifically in response to Arp2/3 network growth, and the interface became smooth and circular. Our assumption/hypothesis was that formation of the smooth and circular interface occurred through contractility of the induced actomyosin ring. However, we agree that we only identified ingredients responsible for forming the smooth and circular interface, and that a physical explanation was lacking. To test the idea that the induced myosin nodes form a contractile ring within an otherwise weakly contractile actomyosin network, we compared simulations of an isolated actomyosin ring with the behaviours of myosin nodes activated by Arp2/3 in an otherwise low contractility network. All nodes of the isolated ring had activity equal to that induced by Arp2/3 in the two-network simulations and were initially arranged as a wide and rough-edged ring. With contractile activity of the nodes, the ring first thinned and smoothened and then the ring constricted centripetally. In the initial rough configuration, the net forces applied to individual nodes occurred at a broad range of angles, but as the ring thinned and constricted, these angles became locally aligned with radii of the contractile ring. We considered this alignment to be a signature of a contractile ring in our simulations. Myosin nodes activated around the circumference of a growing Arp2/3 network displayed a similar signature. Thus, we conclude that the smoothening behaviour is based upon the local induction and activity of a contractile actomyosin ring.These observations are described in detail in an added Results section (starting at line 350) and shown in added Figure 5. We also added a schematic model as Figure 6 to explain the steps of the smoothening process, and refer to this figure in the first paragraph of the Discussion section (starting at line 410).2) Test how sensitive the main results are to initial conditions, and to different parameter values by performing a sensitivity analysis .Sensitivity analyses were also important to add. We performed these analyses to confirm the robustness of our two main findings: (1) that centrifugal expansion of a rough Arp2/3 network against a surrounding and rough actomyosin network is insufficient for forming a smooth interface between them, and (2) that the smoothening occurs through the pushing forces of the Arp2/3 network elevating myosin activity around the interface to form a contractile ring. We conducted these analyses by varying the values of all major parameters of the actomyosin network, the Arp2/3 network, and the network-network interface. Parameters were varied pairwise to create phase diagrams of parameter space. We previously submitted, and continue to include, a phase diagram comparing different values of myosin node activity and myosin node density . The added phase diagrams investigate all other key parameters in the parameter table (Table 1). These analyses indicate that our two main findings are robust to changes in parameters: (1) Arp2/3 expansion is incapable of inducing a smooth and circular interface with a non-mechanosensitive actomyosin network, except with parameter values producing a network-wide increase to actomyosin contractility, and (2) Arp2/3 expansion induces a smooth and circular interface with a mechanosensitive actomyosin network, except under specific and explainable conditions .Please see added Figure 4—figure supplements 1-6 and further explanation in the associated figure legends. Please see references to these figure supplements at lines 296 and 340.3) Describe the model a bit more specifically at the beginning of the result section so the reader has a general sense of how it was implemented.We have added more explanation at the beginning of the Results section, starting at line 126, and continue to refer to the Model Formulation section for full details.4) Using physically relevant units in the text and the table would make it easier to follow and potentially more impactful. Or the authors should explain if there is a good reason to keep those non-physical units.Our preference is to refer directly to properties of the simulations using units of the simulations. We consider our simulations to be their own experimental system. Our approach ensures that it is described as directly and accurately as possible. This approach also allows our simulation data to be more directly applied to a range of contexts. As acknowledged in the reviews, we do provide Table 1 which contains available equivalencies to in vitro and in vivo parameter values. Previously, we only referred to Table 1 in the Model Formulation section, but we now additionally refer to it at the beginning of the Results section (line 146).5) Please provide Matlab files at resubmission.A GitHub link is provided for the MATLAB files, and we continue to provide PDF files with annotated code as supplemental information. Please see line 452.Reviewer #1:Drosophila embryo during pseudo-cleavage. This is an interesting question in the context of how actin networks are organized. To understand interface smoothing, the authors perform "node-based" simulations of the two actin networks. The simulation methods of the two networks follows previously published methods and are validated through comparisons with previous work. For the interface between these networks, the authors invoke some ad hoc rules that are poorly justified form a physical point of view. It is not clear, how much their results depend on this choice of interfacial dynamics.The authors attempt to understand the basis of smoothing interfaces between Arp2/3-based actin networks and actomyosin networks in the syncytial We agree that a lack of understanding of the interface is a limitation of our study, and continue to state this limitation in the paper. However, our rules of node interaction across the interface are relatively simple and based on force balance between nodes directed toward each other because of net forces applied to them. Also, our results were robust to a range of parameter values affecting the interface. Please see added Figure 4—figure supplement 6 and further explanation in the associated figure legend.Whereas the simulation results are quantitatively analyzed, there is essentially no quantification of the experiments, and the comparison between experiment and theory remains qualitative.Unfortunately, smoothening was too challenging to consistently quantify in the experimental data due to variable shapes and intensities of myosin-positive structures within images, and variability of overall signal intensity between samples. To show that the control and Arp3 RNAi data were qualitatively reproducible across embryos, we now provide images of six additional embryos of each genotype. These examples also allow additional comparisons with the simulation results.Please see Figure 3—figure supplement 1.Eventually, the authors propose a set of ingredients that are sufficient to yield smooth interfaces in their simulations. However, a thorough understanding in terms of the physical mechanism underlying the simulation results remains elusive.Please see response under “Essential Revisions”, above.Reviewer #2:[…]Some of the parameters used in all the simulations are set to certain values but those values are often not discussed, and it is unclear to which extent the results of the simulations are sensitive to those parameters.Thank you for this important recommendation. Please see response under “Essential Revisions”, above.The code is provided only as a pdf file which prevents the reader to run the simulations themselves.The authors could test how sensitive their main results are to initial conditions, and to different parameter values by performing a sensitivity analysis Please provide Matlab files at resubmission.They have been provided. Please see response under “Essential Revisions”, above.Things that could be clarified:The authors could explain a bit more how the initial rough patterns of Arp2/3 and acto-myosin zones are generated in the embryo. Is it signaling? Could it be self-organized from a random initial organization by the mechanics too?Signaling is important for the initial patterning, but roles for mechanics are unknown. Specifically, Rho small G protein signaling pathways play essential roles in establishing the initial rough patterns of the cytoskeletal networks. Please see added text at lines 74 and 85-86.They could describe the model a bit more specifically at the beginning of the result section so the reader has a general sense of how it was implemented.Thank you for this suggestion. Please see revised text between lines 126-140.Using physically relevant units in the text and the table would make it easier to follow and potentially more impactful. Or the authors should explain if there is a good reason to keep those non-physical units.Please see response under “Essential Revisions”, above.


As participation is often restricted in children with disabilities, this process might be delayed in adolescents. Investigating profiles of participation for adolescents with and without neurodevelopmental impairments could provide an understanding of which factors relate to high level of participation. The A prospective person-based cohort study design.Five typical trajectories were identified. Trajectories between clusters with high perceived involvement in peer relations were associated with sibling support and family communication. Self-reported neurodevelopmental impairments did not predict participation profiles at certain time points, nor movements between clusters when measuring self-reported attendance and importance in domestic life and in peer-related activities.Perceived sibling support and family communication are important for predicting typical trajectories across clusters in frequency of attendance and the perceived importance of domestic life and peer relations. Type of impairment was less important in predicting typical trajectories. Adolescent participation, Cluster analysis, Neurodevelopmental impairment, Participation trajectories, Person-based design, Self-report ParticuWith increasing age, biological maturity and experience, life situations and thus also life roles change in both number and level of complexity. This includes participating in activities with a primary caregiver and social play activities outside the family, participation in peer relationships and social interactions related to school situations as well as leisure activities. In addition to developmental changes, emotional malfunctioning, i.e., distress and problematic behaviour  may increase during early and middle adolescence . How adoParticipation in everyday life can be viewed as an indicator of health . ChildreChildren with disabilities have the same interests and desires as all children . Nonethea group of conditions with onset in the developmental period. The disorders typically manifest early in development, often before the child enters grade school, and are characterized by developmental deficits that produce impairments of personal, social, academic, or occupational functioning. The range of developmental deficits varies from very specific limitations of learning or control of executive functions to global impairments of social skills or intelligence.One group of individuals known to have difficulties in social interactions are individuals with neurodevelopmental impairments (NDI), e.g., hyperactivity and specific language impairment. According to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) , neurodeHowever, children and adolescents may have difficulties that can be described using criteria for NDI without having symptoms severe enough to prompt a diagnosis . In thisTo understand children and adolescents' experiences of participation in a holistic inter-related manner, the use of person-oriented approaches has been suggested. Studying participation profiles, rather than participation in one specific activity or aggregating participation in different activities to a mean value, gives a broader perspective on children's participation . Using a-What typical trajectories can be found among cluster groups for frequency of attendance and perceived involvement in domestic life and peer relations between two time points?-To what extent do individual and environmental factors predict typical trajectories?-Are adolescents with self-reported neurodevelopmental impairments overrepresented in any of the trajectories?The aim of this study is to investigate typical trajectories across clusters based on self-rated participation patterns in frequency of participation and perceived importance of domestic life and peer-related activities for adolescents with and without self-reported neurodevelopmental impairments. The following research questions were addressed:22.1th and 7th grades. Within the present study, wave 1 and wave 3 are referred to as time one (T1) and time two (T2).This is a person-based longitudinal cohort study using self-reported data from the first and third of five data collections within the ongoing Swedish multidisciplinary research program LoRDIA . The program is designed to follow adolescents in four municipalities in Swedish compulsory schools as well as compulsory schools for adolescents with intellectual disabilities (ID). These municipalities each have between 9,000 and 36,000 inhabitants and are geographically relatively close to one another. The municipalities were chosen as they represent variations in rural and urban density. Two of the municipalities (A and B) have a relatively high degree of internal school migration; adolescents from the minor municipality (B) usually attend senior high school in the somewhat larger municipality (A). Both municipalities are industrial and relatively small. Municipality C is somewhat larger than A and B and close to Sweden's second largest city, while D is smaller and more rural than A, B and C. The data collection started in 2013, when adolescents were in the 62.2The analytical sample consisted of N 916 adolescents  who participated in both the T1 and T2 data collections. The adolescents' mean age was 13.0 (±0.59) years at T1 and 14.34 (±SD = 0.64) at T2. Regarding ethnicity and family situation, 18% came from another country and 82% were living with both parents. Adolescent self-reports revealed that 17% (n = 154)  had self-reported a neurodevelopmental impairment such as attention deficit hyperactivity disorder (ADHD), autism, intellectual disability or speech or language impairment/communication disorder .2.3Data for the present study was collected using paper-based questionnaires where answers were self-rated. At T1 adolescents with ID were given the opportunity to use an adapted form of the questionnaire. The questionnaire was adapted and tested to make the questionnaire accessible for adolescents with intellectual impairments . These adaptations were based on strategies recommended for children and youths with cognitive impairments . Of the The variables used were originally used in scales developed, used, and validated by 2.4Data was collected within schools and the questionnaire took 50–90 min to complete. Members of the research team were present in the classrooms to provide support if necessary. For some of the adolescents with ID or adolescents who spoke another language at home, additional time (approximately 30 min) was required. Participants filled in the questionnaires in classrooms and could ask questions regarding, for example, the meaning of words. A few exceptions for adolescents with ID were made. For example, in one case a staff member of the research team visited an individual who was given the opportunity to fill in the questionnaire at home. This was an option provided by the student's caregiver since it was the student's own wish to take part in the data collection. The adolescents were offered refreshments while completing the form. Adolescents with ID or adolescents with difficulties in reading and writing were provided the option to have the questions read aloud to them in a separate room.2.5As one of the aims of the LoRDIA research program is to investigate mental health and drug misuse, a so-called passive consent method was used, since it was crucial to include adolescents from families where the parents or caregivers might not agree to their children participating in the study. Asking for active consent from caregivers with low socioeconomic status was therefore assumed to put the participation of adolescents who would be able to provide valuable information in line with the aim and scope of the research program at risk. All parents or caregivers were informed via written information sent home about the study, both in Swedish and their native language. At each of the data collection occasions, a member of the research team informed the adolescents about the meaning of the principle of informed consent as well as the possibility of withdrawing from the study at any time without stating reasons for this. Ethical permission for the LoRDIA research program, consent procedure and data collection procedure were approved by the Regional Research Review Board in Gothenburg, Sweden , and additional approvals were obtained for wave II (2014-05-20) (T446-14) and wave III (2015-07-31) (T553-15).2.6Data was analysed by performing a hierarchical cluster analysis (Ward's method) for each of the two time points. Cluster analysis is a technique used for classifying cases into relative groups called clusters .Prior to the cluster analysis a residue analysis was performed in order to identify residual cases (outliers). For both T1 and T2 a nine-cluster solution was chosen. These cluster solutions were chosen after considering factors such as degree of explained variance and the level of homogeneity within the clusters . To opti3A nine-cluster solution was chosen for both T1 and T2, considering frequency of participation and perceived importance in domestic life and peer relations. The Explained Error Sums of Squares (EESS) were 64.76 and 67.74 for the nine-cluster solution after RELOCATE for T1. For T2, the EESS were 62.84 and 66.22 for the cluster solution after RELOCATE.3.1Looking at attendance and involvement in domestic life and peer relations, cluster solutions were made at T1 and T2. The most typical trajectories were investigated further and five significant trajectories between T1 and T2 were identified. All five were characterised as typical trajectories, i.e., trajectories occurring more frequently than expected . Thus, most of the individuals did not follow a more stable typical trajectory. The participation profiles at each time point, i.e., participants' ratings for frequency of participation and perceived importance in domestic life and peer relations at T1 and T2, informed the labelling of the clusters . Within this trajectory, 12% (n = 6) of the adolescents reported that they have an NDI. Adolescents in this trajectory were almost two times more likely to move from cluster 1 to the new cluster 1 at T2, a cluster characterised by higher involvement in peer relations. This trajectory is also characterised by a change in the participation profile between the two time points, with a high increase in the rating of perceived involvement in domestic life at T2.As shown in High perceived involvement in peer relations, was the smallest typical trajectory, with 25 adolescents (60% girls), where 24% (n = 6) of the adolescents had a self-reported NDI. As shown in Higher perceived involvement than frequency, moved from cluster 3 at T1 to a similar cluster (cluster 9) at T2; both identified by higher perceived involvement than perceived frequency. In this trajectory, there were 26 adolescents, of whom 65% were girls and 23% (n = 6) had a self-reported NDI. For this trajectory there was a similar cluster profile at both T1 and T2, characterised by higher ratings of perceived importance of domestic life and peer relations than frequency of attending.Trajectory 2, labelled Lower frequency of involvement in domestic life, consisted of 33 adolescents who were three times more likely to move from cluster 5 at T1 to cluster 2 at T2. There were 61% girls and 18% (n = 6) of the adolescents self-reported an NDI. This trajectory was characterised by a non-stable cluster profile from T1 to T2, with an increase for the ratings of both frequency and perceived involvement for domestic life activities and peer relations.Trajectory 4, labelled High increase in domestic life involvement, moved from a cluster with lower frequency in domestic life to a cluster identified as higher in involvement but still low in frequency in domestic life. The total number of adolescents in this trajectory was 33 (52% girls). This trajectory had fewer adolescents with an NDI than the other trajectories (N = 3). A high increase in ratings for perceived involvement in domestic life and a slight decrease in the rating for the frequency of peer relations from T1 to T2 characterised this trajectory.Adolescents in Trajectory 5, labelled 3.2The associations between individual factors  and environmental factors  and participation trajectories are shown in Lower frequency in domestic life (#4) than to belong to the reference group High frequency of peer relations (#1). That is, the more mature one perceives oneself, the higher the probability of belonging to a trajectory with lower frequency and perceived involvement for domestic life activities, rather than belonging to a trajectory with high frequency of peer relations.Adolescents with high ratings of the experience of time and self were six times more likely to belong to the trajectory High frequency of involvement in peer relations (#1) than trajectory 2, thus High perceived involvement in peer relations and 5, and thus High increase in domestic life involvement. Adolescents who reported constructive communication in the family and perceived involvement in school were more likely to belong to the High perceived involvement in peer relations trajectory (#2). Perceived involvement in school was also positively associated with belonging to trajectory 3, thus Higher perceived involvement than frequency.Furthermore, adolescents with high levels of sibling support were more likely to belong to the trajectory Adolescents with an NDI were evenly distributed within the typical trajectories. In one trajectory only three adolescents with an NDI were represented, versus six in the others. This could be a major difference, as it is half the amount present in the others. However, the fact that 17% of all adolescents with an NDI were represented in these five trajectories, and quite evenly distributed, indicates that this group pattern of participation is similar to those of typical development. For the typical group, 18% of all adolescents followed one of these five typical trajectories.High perceived involvement in peer relations (#2) and Higher perceived involvement than frequency (#3) were relatively stable regarding the participation profile for self-reported participation in domestic life and peer-related activities. The trajectories High frequency of peer relations (#1) and Lower frequency of involvement in domestic life (#4) had a somewhat altered cluster profile at T2, where trajectory 1 had more similar ratings at T2 and trajectory 4 had a distinct increase in peer involvement at T2. Further, the trajectory Lower frequency of involvement in domestic life (#4) was associated with high ratings of time and self . Further, the trajectory High perceived involvement in peer relations (#2) was associated with high levels of sibling support, positive perceived family communication and perceived involvement in school. Belonging to the High increase in domestic life involvement (#5) trajectory was associated with experiencing higher levels of sibling support.In sum, the typical trajectories labelled 4Using a person-oriented design, this study investigated typical trajectories between cluster profiles of participation related to frequency of attendance and perceived importance of domestic life and peer-related activities. As only typical trajectories were identified, the clusters represented were a small share of the total population, namely 18% and 17% of the total NDI population. Results indicate that the participation profiles were relatively stable over a two-year period. Gender seems to have a more prominent role in predicting trajectories than NDI. There is an overrepresentation of girls in the typical trajectories except in trajectory #5.High perceived involvement in peer relations (#2) and Higher perceived involvement than frequency (#3), are characterised by having stable cluster profiles at T1 and T2 but vary in frequency of attendance and perceived involvement in peer relations in the cluster profiles. Adolescence consists of a time in life when individuals face challenges such as alterations in social relationships with both family and peers as well as physical and emotional changes associated with maturation  and High increase in domestic life involvement (#5) are characterised by higher or lower involvement in domestic life in their cluster profiles from T1 to T2. A possible reason could be that individuals in trajectory 4 experience themselves to be more mature. The assumption drawn is then that an increase in domestic life involvement is due to increased maturation leading to more responsibilities taken at home. Trajectory 5 is characterised by lower odds in all factors. As this group was, both at T1 and T2, focused on high participation in peer relations, one can argue that this group is more peer-oriented than family- or school-oriented, even though they have an increase in domestic life involvement at T2.The trajectories High frequency of peer relations trajectory (#1) move to a cluster profile characterised by higher involvement both in peer relations and domestic activity at T2.Although the participation patterns seem to be relatively stable over time, as indicated by the stability in cluster formations (trajectories 2 and 3), some adolescents change their participation pattern between T1 and T2 . Individuals in trajectory 4 move to a cluster formation at T2 with higher involvement in domestic activities. One explanation for this might be that as one gets older and more mature family demands increase in relation to domestic life activities and domestic life activities are performed more on a routine base. Regarding peer relations, there is perhaps already a relatively established social network. Adolescents in the Lower frequency of domestic life (#4). This might imply that adolescents experiencing themselves to be more mature will over time be less involved in family life activities. Another factor that was related to trajectory was sibling support. Sibling relationships in adolescence have been proven to be important for psychosocial functioning (High frequency of peer relations (#1) than High perceived involvement in peer relations (#2) and High perceived involvement in domestic life (#5). This indicates that adolescents who perceive themselves as having a supportive relationship with their siblings also engage more in relations with peers. This parallels another study where results demonstrated that positive sibling relations seem to act as protective factors for social competence (High perceived involvement in peer relations (#2). This trajectory had a stable cluster profile when time points were compared. Parental knowledge of their adolescents' activities as well as open communication between parents and their adolescent children is often considered a protective factor in adolescents' psychosocial development  was associated with belonging to the trajectory ctioning . In the mpetence . Arguablelopment . When paelopment . Thus, eLower frequency in domestic life (#4). This was somewhat surprising, given the assumption that the more mature one perceives oneself, the more frequently one takes part in domestic life activities, in contrast to what these results indicate. The result may rather indicate that adolescents who perceive themselves as more mature spend more time with peers and perceives domestic life activities as more important.Results also indicate that the more mature one feels, the higher the probability of belonging to the trajectory In sum, factors based on the perceived environment in the family are more prominent in predicting trajectories in participation in domestic life and peer relations than individual factors such as type of impairment. Adolescents with self-reported NDIs were not overrepresented in any of the trajectory groups, and they were very few.Most adolescents did not follow a typical trajectory between clusters. This result indicates that participation profiles are relatively unstable for most adolescents. This supports earlier studies reporting that adolescence is a period of change. However, for a larger proportion than expected, namely 18%, clear pathways were found. These pathways were fairly stable over the two-year period. Moreover, they are characterised by fairly high levels of participation in domestic and peer involvement. Trajectory 1 does perhaps have more moderate participation, and trajectory 3 seems to be more home-oriented than peer-oriented, with lower participation in peer activities. Nonetheless, most of these clusters and trajectories are moderate to high in their level of participation.4.14.1.1In this study the choice was made to study the most typical trajectories with the consequence that the less typical  trajectories were not studied, which should be considered a weakness. This is also why only 18% of the total population follow typical trajectories. This means that adolescents with an NDI do not appear in typical trajectories more frequently than expected, in comparison to adolescents without an NDI, with the implication that the trajectories adolescents with an NDI take remains a question that should be further investigated. The data used in the current study is based on self-ratings and it has not been possible to determine whether adolescents have a confirmed diagnosis or not. This should be taken into consideration when interpreting the results of this study. However, the use of self-reports makes it possible to capture adolescents' own opinions about their everyday situation, regardless of whether or not they have a diagnosis; individuals who report subthreshold difficulties (under the threshold for the diagnostic criteria) may experience difficulties affecting everyday functioning .In addition, in some cases the participation outcomes (the indices for frequency and perceived involvement in domestic life and peer relations) had relatively low internal consistency, which could arguably be a consequence of the complexity of the participation concept as well as the complexity of measuring participation. The homogeneity coefficient was above 1 in some of the clusters at T1 (cluster 9) and at T2 , which is probably also a consequence of the relatively low internal consistency in some of the outcome variables in the cluster analysis. This study uses a total population-based sample which should be considered a strength. Adolescents with an NDI were, however, very few in relation to the total sample, which should also be taken into consideration when the interpreting the results of the current study, since this might lessen the generalisation potential of the results.5Self-reported participation is relatively stable when measuring two points in time approximately 2 years apart. Type of impairment did not predict participation trajectory. Environmental factors such as family communication are more important predictors for the identified typical trajectories, indicating that interventions aiming to enhance participation should be directed towards the persons surrounding the individual, including siblings.6When designing interventions aiming at increasing participation in domestic life and peer relations for adolescents with and without neurodevelopmental impairments it is important to include environmental factors such as sibling support and communication patterns in the family. This implicates not only the importance of an interdisciplinary approach but also the importance of identifying factors that affect participation and which are malleable by intervention. Family functioning is important for the longitudinal trajectories of participation in adolescents. It also implies that professionals need to involve family in data collection, not only regarding the adolescent but also aspects of family life. Having a self-reported neurodevelopmental impairment was not strongly related to type of participation trajectory, which indicates the need to assess the proximal environment independent of disability status of the adolescent.Frida Lygnegård: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.Mats Granlund, Lilly Augustine, Karina Huus: Conceived and designed the experiments; Analyzed and interpreted the data; Wrote the paper.Sabina Kapetanovic: Contributed reagents, materials, analysis tools or data; Wrote the paper.10.13039/501100004359Swedish Research Council (VR); the Swedish Research Council for Health, 10.13039/501100006636Working Life and Welfare (FORTE); Sweden’s Innovation Agency (VINNOVA); and the 10.13039/501100001862Swedish Research Council Formas (259-2012-25), as well as the Sävstaholm Foundation (ST-2014-023) and the Sunnerdahl Disability Foundation (22/17).This work was supported by a combined grant from four Swedish research foundations: the Data will be made available on request.The authors declare no conflict of interest.No additional information is available for this paper.


Keratin intermediate filaments are an essential and major component of the cytoskeleton in epithelial cells. They form a stable yet dynamic filamentous network extending from the nucleus to the cell periphery, which provides resistance to mechanical stresses. Mutations in keratin genes are related to a variety of epithelial tissue diseases. Despite their importance, the molecular structure of keratin filaments remains largely unknown. In this study, we analyzed the structure of keratin 5/keratin 14 filaments within ghost mouse keratinocytes by cryo-electron microscopy and cryo-electron tomography. By averaging a large number of keratin segments, we have gained insights into the helical architecture of the filaments. Two-dimensional classification revealed profound variations in the diameter of keratin filaments and their subunit organization. Computational reconstitution of filaments of substantial length uncovered a high degree of internal heterogeneity along single filaments, which can contain regions of helical symmetry, regions with less symmetry and regions with significant diameter fluctuations. Cross-section views of filaments revealed that keratins form hollow cylinders consisting of multiple protofilaments, with an electron dense core located in the center of the filament. These findings shed light on the complex and remarkable heterogenic architecture of keratin filaments, suggesting that they are highly flexible, dynamic cytoskeletal structures. Keratin Intermediate Filaments (KIFs) are an essential component of the cytoskeleton of epithelial cells. KIFs are classified as type I and type II Intermediate Filament (IF) proteins, according to their sequence . KeratinKeratin proteins are composed of three domains: a highly conserved α-helical central rod domain, known to facilitate filament assembly, and intrinsically disordered head and tail domains. The latter are highly post-translationally modified and are regarded as essential for regulatory functions and filament stability . Keratin11 tetramers, where the 1B domains of the rod of two adjacent dimers interact in a half-staggered, antiparallel arrangement  and Cryo-Electron Tomography (cryo-ET) . Since tKrt6a and the Krt6b gene, which share 92.6% sequence identity . Although a small amount of wild-type Krt6b DNA was retained  . The ghoKeratins form a complex filamentous network, including thick bundles containing numerous filaments, meshworks, in which filaments are often crossing and interacting with each other, as well as long stretches of individual filaments . KeratinTo obtain deeper insights into the architecture of keratin filaments, we extracted 55 nm long straight keratin segments picked along filaments in ~1700 cryo-EM micrographs and subjected them to structural averaging by single particle data processing . A helicIn order to determine the repeating unit, that is the pitch of the helical patterns observed in the class averages we calculated autocorrelation spectra for each helical class . Using tThe 2D class averages allowed us to identify structural differences in 55 nm long keratin segments. To understand how these structural features are organized at the level of long keratin filaments, it was important to determine how the class averages are arranged along keratin filaments which are up to several hundreds of nanometers in length. For this purpose, we utilized a back-mapping strategy that permits the computational reconstitution of the original filament out of 2D class averages . TherefoThe appearance of these computationally reconstituted keratin filaments is very heterogenous . Overallxy plane .Interestingly, the computationally reconstituted filaments revealed that helical regions with different pitch lengths, identified in the 2D class averages , can co-Overall, computationally reconstituted keratin filaments reveal an enormous amount of structural heterogeneity . Every fA careful analysis of our datasets revealed several cryo-EM micrographs and multiple cryo-tomograms (21 out of 44) which contain KIFs that undergo a 90° turn along the thickness of the sample and therefore allow the observation of direct perpendicular cross sections of the filaments . This beTo study the number of protofilaments in more detail, we selected 710 cross-sectional views of filaments found within the cryo-tomograms, extracted central slices and subjected them to 2D classification, revealing a symmetric hexameric class . Six indFinally, to get an impression of a mature keratin filament in three dimensions, we generated a low-resolution 3D model of a keratin filament from our single particle dataset of 55 nm long segments using the Relion software package . By randKeratin intermediate filaments are major components of the cytoskeleton that are involved in many cellular processes . HoweverThe K5/K14 IFs filaments are known to assemble in the cell periphery  to form xy plane and form a wavy network in all three dimensions. Cryo-tomograms of ghost cells allowed us to follow individual filaments through different heights of the cell and show that the filaments can undergo 90° turns within a thickness of <300 nm . Confluent cells were trypsinized using 2.5 x trypsin/EDTA solution  and re-seeded at a maximum splitting ratio of 1:2. To knock-out the Krt6a and Krt6b genes, cells were transfected with the pX458 (pSpCas9(BB)−2A-GFP) plasmid (Addgene) carrying a GFP-tagged Cas9 and a guideRNA insert targeting both the Krt6a and Krt6b gene (guideRNA sequence: GAGCCACCGCTGCCCCGGGAG). Transfection using electroporation was performed according to the manufacturer’s protocol using a P3 primary cell 4D-Nucleofector kit (Lonza) and program 138 for human keratinocytes, followed by another round of transfection using jetPRIME (Polyplus transfection). Next, genomic DNA was extracted from clonal cell lines using the GenElute Mammalian Genomic DNA kit (Sigma-Aldrich) and the Krt6a and Krt6b gene fractions where the indel mutations were expected were amplified by PCR. PCR fragments were sequenced (Microsynth) and the indel mutation spectrum was analyzed using the TIDE webtool (https://tide.nki.nl/). The K5/K14_1 clone was identified as homogenous K6a knockout and heterogenous K6b knockout and was therefore used for all studies. To further verify the knockout, PCR fragments were cloned into the pGEM-T Easy vector  and amplified in DH5α cells. Bacterial clones carrying individual gene sequences of Krt6a or Krt6b were picked and amplified, plasmids were extracted and sequenced (Microsynth). By analyzing 19 Krt6a and 22 Krt6b sequences, the homogenous K6a and heterogenous K6b knockout were verified.Mouse keratinocytes lacking the entire type I keratin cluster (KtyI KO) but stably transfected with K14  were aut2. For staining with keratin antibodies, cells were fixed for 5 min using ice-cold 99.9% anhydrous methanol . Non-specific antibody binding sites were blocked by incubating the cover slips for 30 min in blocking buffer ). Next, cover slips were incubated for 1 hr at room temperature with mouse anti-mouse Keratin 14 , rabbit anti-mouse Keratin 5  or rabbit anti-mouse Keratin 6a  in 1% BSA in 0.1% PBS-T. It should be noted here that the K6a antibody used is a polyclonal antibody, which is suspected to bind to the K6b protein as well, due to their high sequence identity (92.6%). After 3x 5 min washing steps in PBS, cover slips were incubated with Cy3 donkey anti-rabbit  or FITC donkey anti-mouse  secondary antibodies in 1% BSA in 0.1% PBS-T. Cells were washed 3x for 5 min in PBS, before nuclei were stained with Hoechst 33342  for 10–20 min at room temperature. After a final wash step 3x for 5 min in PBS, the cover slips were mounted on glass slides with Dako mounting medium  or Prolong Glass Anti-Fade . Confocal imaging for The KtyI KO K14 and K5/K14_1 cells were seeded on Collagen I coated glass cover slips in cell culture dishes and incubated overnight at 32°C and in 5% CO2. The grids were rinsed in washing buffer , cells were permeabilized for 15–20 s in permeabilization buffer , and rinsed again in washing buffer. Next, the grids were incubated with 2.5 units/µl benzonase  in washing buffer for 30 min and washed in PBS before vitrification in liquid ethane using a manual plunge freezing device. For cryo-ET samples, 10 nm gold fiducial markers  were added to the grids right before freezing.K5/K14_1 cells were seeded on glow-discharged Collagen I coated holey carbon gold EM grids  and incubated overnight at 32°C and in 5% CO2 for the ×22,665 dataset, ~41 e/Å2 for the ×28,571 and ~84 e/Å2 for the ×46,511 dataset. In total, data were collected from ~60 ghost cells. Micrographs acquired at a magnification of 22,665 x were used for most experiments conducted in this study, as stated below. The datasets acquired at ×46,551 and ×28,571 magnification were used to visualize the keratin cytoskeleton in closer detail and micrographs from these datasets are shown in The grids were analyzed using a 300 kV Titan Krios electron microscope (Thermo Fisher) equipped with a K2 Summit direct electron detector (Gatan) mounted on a post-column energy filter (Gatan). Cryo-EM micrographs were acquired in zero-loss energy mode using a 20 eV slit. Data were recorded with SerialEM 3.5.8 in low-dose mode . Overvie2. SerialEM 3.5.8 in low dose mode was used for data acquisition . The filament diameter was measured by plotting vertical intensity line-profiles of all classes using MATLAB and measuring the area where the intensity lies above zero.Intensity line-profiles of each class were generated by averaging all lateral sections through the segment. OriginPro 2018 software (OriginLab Corporation) was used to plot the diameter distribution. Instead of plotting the number of classes, which was set to a fixed value, the number of particles in each class was plotted, as it reflects how many particles with a certain diameter are present in the dataset. A mean intensity line-profile for Segments with a box size of 36 nm were used for computational filament reconstitution. Filament reconstitution was performed as previously reported  and descActin filaments were processed identically to keratin filaments to guarantee comparability. To generate a template for autopicking, 22,228 actin particles were picked manually as start-to-end helices, extracted with a box size of 164 pixels (~36 nm) and 2D classified twice to create classes with straight actin segments. These classes served as a reference for automated picking of 693,903 particles. Particles were extracted in boxes of 164 pixels, corresponding to ~36 nm, with an inter-box distance of 50 Å. Multiple rounds of 2D classification were performed, using a spherical mask of 356 Å. A total of 405,044 particles from the highest resolved 2D classes were used for 3D classification into five classes. The highest resolved 3D class, containing 174,954 particles, was subjected to 3D refinement.2.The final unmasked map showed a resolution of 7.38 Å, based on the gold standard Fourier shell correlation (FSC) 0.143 criterion . The strTilt series were processed using the IMOD workflow, including contrast transfer function (CTF) correction . For visTo generate computationally reconstituted filaments a back-mapping strategy was pursued in MATLAB, using the ~36 nm long keratin segments which were used for 2D classification. First, all particles belonging to the same filament were grouped. Filament assignments were made based on the helical tube ID defined by RELION for every particle. Next, all particles belonging to the same filament were sorted in ascending order based on their picking coordinates. Then, their corresponding 2D class images were inversely transformed, so that their orientation matches the original orientation of the raw segments in the cryo-EM micrographs. Next, the 2D class images were plotted at the original coordinates of the particles. To remove background noise, the classes were masked in the y-direction and only the central 132 Å were plotted. Since particles were picked with inter-box distances of 50 Å, while 2D classes have a box size of 360 Å, neighboring segments would strongly overlap. To avoid this, classes were cropped to not extend into neighboring particle positions, and only a small amount of overlap of <four classes with soft edges was allowed to avoid cropped edges in slightly bent filaments. Reconstituted filaments were normalized to equal intensity. Next, a straightening procedure was applied as previously described to extract, align and straighten the reconstituted filaments . ValiditPlots representing the order of helical and straight segments along individual filaments, represented by colored circles, were generated in MATLAB as previously described . 2D clas305,495 uniform keratin segments from 55 nm boxes were selected by 2D classification  and used 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) Acceptance summary:In this study, Weber et al. study the structure of keratin intermediate filaments (KIFs) in detergent extracted 'ghost' cells using cryo-EM. To limit compositional heterogeneity the authors generate a cell line which contains only K5/K14 filaments. They show the KIFs vary in diameter and protofilament helicity. The authors also use cryo-electron tomography to show that KIFs contain density in their center. In some cases, six protofilaments are clearly visible in the cross sections but there also appears to be heterogeneity in their number. This data is a first in the field of keratin research, and provides a much needed framework to understand the structure, properties, and roles of keratin filaments.Decision letter after peer review:eLife. Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Anna Akhmanova as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Helen Foster (Reviewer #2).Thank you for submitting your article "Structural heterogeneity of cellular K5/K14 filaments as revealed by cryo- electron microscopy" 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. The reviewers agreed that the work is an important step forward for the keratin field and is well executed. They suggest only textual revisions. Please see their full reviews below.Essential Revisions (for the authors):1) The discussion of the variable length repeating patterns is not currently clear. In the results (p. 9 and 12), the authors conclude that the observed variability is due to change in Z-height of filament and associated tilt of the filament along its axis. However, the differences in helical pattern are included as a feature of protofilament heterogeneity in the discussion (line 382). Based on the current data, the differences detected could be due to changes in Z-height or true variation in protofilament arrangement. Ideally this should be clarified through classification of 3D sub volumes of the cryo-ET data but this will be technically challenging. I suggest the authors conclude both options are possible in the results and limit the discussion of protofilament arrangement to differences in straight vs. twisted, which are clear in the data.2) How rigorous are the biochemical analyses that were conducted to establish that K5 is the only type II keratin expressed in the recombinant mouse keratinocytes? Also, have the authors effectively ruled out that other IFs, e.g., vimentin (nestin?), could be expressed in some of the keratinocytes analyzed?3) How many keratinocytes have been sampled to constitute the bank of images subjected to processing and analysis? What criteria were considered when opting to include/exclude cells from the analysis?4) Figure 1 relates that the sampling of filaments for analysis was taken at the periphery of the cell, as expected. This is where keratin filament assembly takes place, certainly in cultured cells, as originally shown by Rudolf Leube in 2004 (MBoC) and confirmed for additional cell types including mouse skin keratinocytes in primary culture . Therefore, it may be that the heterogeneity in filament structure reflect, to a degree, an immature or yet to be completed assembly state for the fibers. Another potential determinant of the hypervariable structure of the fibers may stem from the use of detergents to prepare cell ghosts. Yet another contributing factor may be that individual/isolated cells were included in the study, whereas keratinocytes are naturally occurring as multicellular assemblies. Surprisingly, these potential factors are not discussed in the manuscript – at least, not as much as they should.5) Aside from the role of tilting adeptly described by the authors, could there be a relationship between the size of the repeat distance of the axial helical pattern and filament diameter? Related to this, could the filaments or filament segments showing a longer repeat distance be "stretched", or those with a shorter repeat distance be "compressed"? This is a very interesting aspect of the study.6) The authors should relate the caveats and/or assumptions associated with the approach they used to "reconstitute" the filaments (lines 227-240). I thought that as actually reconstituted filaments from purified K5 and K14 proteins – including that reference would have been very exciting.7) The variable sub-architecture of filaments may be a key determinant that underlies the property of self-organization of keratin filaments – the latter has been best characterized, biochemically, in a 2002 MBoC paper by Yamada et al. 2009 J Cell Biol paper by Lee and Coulombe. Upon a modest shift in pH , K5-K14 undergo bundling to a remarkable degree, a property the significantly enhances their micromechanical properties . Please consider discussing.8) Lines 351-352. Given all the biases that have gone into selection of individual fibers for analysis, I question the rationale for spending so much time discussing persistence length, given that in this regard this current study contributes little to what was already known in that regard.9) The observation of a "central core", if this is real, is a game changer in the field. Could the core density be "just another protofilament" that happens the be centrally located in cross-section? Does this core show a helical pattern along the main axis of the fiber? Is the core present whether the filament are comprised of protofilaments showing a heliocal pattern, or only in filaments for which the protofilaments are "straight? Finally, could the core be related to the end domains?  Here, it is important to recognize that Lars Norlen (J Invest Dermatol 2004) has reported on such a central core in native keratin filaments in cross-section when analyzing terminally differentiated keratinocytes of epidermis using cryoEM analysis of sections prepared from flash-frozen, vitrified skin tissue. His findings should be discussed.10) What about the unstructured end domains at the N- and C-termini of K5 and K14? Any insight about where they may be located? The head domains, in particular, are as "large" in primary structure as are subdomain 1B and coil 2.11) Please comment on how this work compares to two earlier reports in the literature. I.e. the cryo-EM of vimentin filaments , that shows an octameric, i.e. protofibrillar organization of IF, in agreement with the keratin work published by Ueli Aebi (JCB 1983). In the latter paper, a four-stranded helical arrangement of protofibrils is shown. Also, the assembly process via unit-length filaments gives a symmetry of filaments according to their repeat-length of 43 nm, etc.Reviewer #1 (Recommendations for the authors):Main issues to considerHow rigorous are the biochemical analyses that were conducted to establish that K5 is the only type II keratin expressed in the recombinant mouse keratinocytes? Also, have the authors effectively ruled out that other IFs, e.g., vimentin (nestin?), could be expressed in some of the keratinocytes analyzed? Given what is at stake here, might it not be desirable to conduct a MS-based survey of all the proteins contained in the cell ghosts subjected to cryoET analyses?How many keratinocytes have been sampled to constitute the bank of images subjected to processing and analysis? What criteria were considered when opting to include/exclude cells from the analysis?Figure 1 relates that the sampling of filaments for analysis was taken at the periphery of the cell, as expected. This is where keratin filament assembly takes place, certainly in cultured cells, as originally shown by Rudolf Leube in 2004 (MBoC) and confirmed for additional cell types including mouse skin keratinocytes in primary culture . Therefore, it may be that the heterogeneity in filament structure reflect, to a degree, an immature or yet to be completed assembly state for the fibers. Another potential determinant of the hypervariable structure of the fibers may stem from the use of detergents to prepare cell ghosts. Yet another contributing factor may be that individual/isolated cells were included in the study, whereas keratinocytes are naturally occurring as multicellular assemblies. Surprisingly, these potential factors are not discussed in the manuscript – at least, not as much as they should.Aside from the role of tilting adeptly described by the authors, could there be a relationship between the size of the repeat distance of the axial helical pattern and filament diameter? Related to this, could the filaments or filament segments showing a longer repeat distance be "stretched", or those with a shorter repeat distance be "compressed"? This is a very interesting aspect of the study.The authors should relate the caveats and/or assumptions associated with the approach they used to "reconstitute" the filaments (lines 227-240). I thought that has actually reconstituted filaments from purified K5 and K14 proteins – including that reference would have been very exciting.The variable sub-architecture of filaments may be a key determinant that underlies the property of self-organization of keratin filaments – the latter has been best characterized, biochemically, in a 2002 MBoC paper by Yamada et al., 2009 J Cell Biol paper by Lee and Coulombe. Upon a modest shift in pH , K5-K14 undergo bundling to a remarkable degree, a property the significantly enhances their micromechanical properties .Lines 351-352. Given all the biases that have gone into selection of individual fibers for analysis, I question the rationale for spending so much time discussing persistence length, given that in this regard this current study contributes little to what was already known in that regard.The observation of a "central core", if this is real, is a game changer in the field. Could the core density be "just another protofilament" that happens the be centrally located in cross-section? Does this core show a helical pattern along the main axis of the fiber? Is the core present whether the filament are comprised of protofilaments showing a heliocal pattern, or only in filaments for which the protofilaments are "straight? Finally, could the core be related to the end domains?  Here, it is important to recognize that Lars Norlen (J Invest Dermatol 2004) has reported on such a central core in native keratin filaments in cross-section when analyzing terminally differentiated keratinocytes of epidermis using cryoEM analysis of sections prepared from flash-frozen, vitrified skin tissue. His findings should be discussed.What about the unstructured end domains at the N- and C-termini of K5 and K14? Any insight about where they may be located? The head domains, in particular, are as "large" in primary structure as are subdomain 1B and coil 2.Reviewer #2 (Recommendations for the authors):This paper clearly shows that cellular keratin intermediate filaments are highly heterogenous. I only have one main point for the authors to clarify.Main point:– The discussion of the variable length repeating patterns is not currently clear. In the results (p. 9 and 12), the authors conclude that the observed variability is due to change in Z-height of filament and associated tilt of the filament along its axis. However, the differences in helical pattern are included as a feature of protofilament heterogeneity in the discussion (line 382). Based on the current data, the differences detected could be due to changes in Z-height or true variation in protofilament arrangement. Ideally this should be clarified through classification of 3D sub volumes of the cryo-ET data but this will be technically challenging. I suggest the authors conclude both options are possible in the results and limit the discussion of protofilament arrangement to differences in straight vs. twisted, which are clear in the data. Essential Revisions (for the authors):1) The discussion of the variable length repeating patterns is not currently clear. In the results (p. 9 and 12), the authors conclude that the observed variability is due to change in Z-height of filament and associated tilt of the filament along its axis. However, the differences in helical pattern are included as a feature of protofilament heterogeneity in the discussion (line 382). Based on the current data, the differences detected could be due to changes in Z-height or true variation in protofilament arrangement. Ideally this should be clarified through classification of 3D sub volumes of the cryo-ET data but this will be technically challenging. I suggest the authors conclude both options are possible in the results and limit the discussion of protofilament arrangement to differences in straight vs. twisted, which are clear in the data.We thank the Reviewer for this comment. Indeed, the variations detected in the repeating pattern could be attributed both to filament tilting or/and to variations in protofilament arrangement. In the revised manuscript, we emphasize this point in the results and Discussion sections, where we focus on the obvious heterogeneity of keratin filaments, i.e., variability in diameter, alternating helical and straight filament patterns.2) How rigorous are the biochemical analyses that were conducted to establish that K5 is the only type II keratin expressed in the recombinant mouse keratinocytes? Also, have the authors effectively ruled out that other IFs, e.g., vimentin (nestin?), could be expressed in some of the keratinocytes analyzed?The cell line we used for the Krt6a and Krt6b knockout is a well-characterized and authenticated cell line, generated in the Magin lab, termed KtyI KO K14 cell line. The KtyI KO keratinocytes were extracted from knockout mice lacking the entire type I keratin cluster. After lentiviral transduction of the Krt14 gene, these KtyI KO K14 keratinocytes were able to re-form a keratin cytoskeleton meshwork, consisting of K5/K14 filaments and K6/K14 filaments. Expression of non-keratin IFs, e.g. vimentin, was excluded by analyses performed in the Magin lab. In the KtyI deficient embryos, vimentin expression was excluded by RT-PCR, in keratinocytes, illumina arrays were performed that excluded the expression of non-keratin IFs . These references are included and we have now clarified this point in the revised manuscript.These analyses showed that K5, K6a, K6b and K14 are the only intermediate filaments expressed in KtyI KO K14 cells. After the CRISPR/Cas9 knockout of the Krt6a and Krt6b gene, the knockout was verified by genomic DNA analysis of the Krt6a and Krt6b genes, which revealed frame-shift mutations . This produces a homogenous K6a and a heterogenous K6b knockout. However, immunostaining revealed that no K6b/K14 filaments are assembled . We could not rule out that non-filamentous K6b protein is present in the K5/K14_1 cells, but it does not assemble into filaments and therefore does not interfere with our analysis. Furthermore, non-filamentous soluble keratin proteins would be removed during the cell permeabilization step and are therefore not present in the ghost cells. It can be concluded that K5/K14 filaments are the only IFs present in the sample analyzed for this study. We highlighted this in the Results section.3) How many keratinocytes have been sampled to constitute the bank of images subjected to processing and analysis? What criteria were considered when opting to include/exclude cells from the analysis?For the different datasets, micrographs were collected on a total of ~ 60 ghost cells. The dataset at 22,655x, which was used for most experiments including 2D classifications and computational reconstitution of long keratin filaments was acquired on ~ 20 ghost cells.No cell that was used for data collection was excluded at any later stage of analysis. Data were recorded at positions where the thickness of the ghost cells allowed cryo-EM analysis. Overview images of entire ghost cells were acquired prior to data acquisition, in which the filaments were identified. Individual micrographs were excluded if they contained no keratin filaments or if the cellular environment was so densely packed that no individual keratin filaments could be identified. Additionally, only high-quality images were used, assessed by CTF estimation (CTF information exceeds 7.5 Å).We included the information above in the Methods section.4) Figure 1 relates that the sampling of filaments for analysis was taken at the periphery of the cell, as expected. This is where keratin filament assembly takes place, certainly in cultured cells, as originally shown by Rudolf Leube in 2004 (MBoC) and confirmed for additional cell types including mouse skin keratinocytes in primary culture . Therefore, it may be that the heterogeneity in filament structure reflect, to a degree, an immature or yet to be completed assembly state for the fibers. Another potential determinant of the hypervariable structure of the fibers may stem from the use of detergents to prepare cell ghosts. Yet another contributing factor may be that individual/isolated cells were included in the study, whereas keratinocytes are naturally occurring as multicellular assemblies. Surprisingly, these potential factors are not discussed in the manuscript – at least, not as much as they should.We thank the Reviewer for this comment.Although much of the data was acquired close to the cell periphery, most images were acquired several microns into the cells, while other micrographs were collected deeper within the cell; sometimes in close proximity to the nucleus. Thus, our data was not only acquired close to the plasma membrane, but reflects keratin filaments from most parts of the cell. Further, filaments with obvious ends were excluded from our analysis. This is now clarified in the Discussion section.We showed that the structure of long, single filaments is modulated along their long axis, and the observed heterogeneity occurred not only between, but especially within individual filaments. It is unlikely that all of the 4,460 filaments that we reconstituted in silico  are not fully assembled, especially since some were found close to the cell nucleus.Therefore, we believe that the changes in structure reflect an intrinsic property of keratin IFs throughout the cell. However, it may be that our structural analysis includes a subset of filaments in different states of assembly, but we did not detect a unique structural motif that stood out in any subcellular location. However, in light of this comment, we discuss this possibility in the Discussion section.Traditionally, structural biology relies on successful purification which involves multiple steps, some of which may include detergents or other chemicals. Here we have minimized this procedure down to a matter of minutes in order to reduce the risk of structural changes. The diluted detergent (0.1 % Triton X-100) was used for 15-20 seconds, to prepare ghost cells which contained typical keratin filament networks. To assess the effect of the detergent treatment on protein structures we analyzed actin filaments from the same dataset and could show that the actin structure is unaltered and can be resolved to 6.1 Å . Moreover, previous studies on lamins, a type V intermediate filament, showed, that the structure of lamin filaments is not altered after a similar detergent treatment when compared to cryo-FIB milling and tomography of unextracted cells . Therefore, we have concluded that it is unlikely that the detergent treatment alters the keratin IF structure significantly. In line with this reviewer’s comment, we elaborate on this in the Discussion section.In our experiments, cells were not studied in isolation. Keratinocytes require close associations with neighboring cells, so they were always cultured at high densities (minimum of 50%) on EM grids. Typically, in our preparations cells are directly attached to other cells . Nevertheless, it may be possible that the KIF network organization in the cultured keratinocytes is different than in keratinocytes which are grown in denser monolayers or in tissues. Therefore we do not draw conclusions about the keratin IF network organization. With this approach it is unlikely that the structure of individual keratin IF themselves is altered.5) Aside from the role of tilting adeptly described by the authors, could there be a relationship between the size of the repeat distance of the axial helical pattern and filament diameter? Related to this, could the filaments or filament segments showing a longer repeat distance be "stretched", or those with a shorter repeat distance be "compressed"? This is a very interesting aspect of the study.This is a very interesting point. We re-analyzed our data and compared the diameters of 2D classes with differences in the repeating pattern, but we could not find a correlation between the diameter and the length of the repeating pattern. Actually, the 2D classes which show a helical repeating pattern are all ~ 10 nm in diameter. The very wide (~13 nm) or very thin (~9.2 nm) classes do not show a clear repeating pattern, so the comparison is not straightforward.It is still possible that the filament segments with longer repeat distances are “stretched” and those with shorter repeat distances are “compressed”. However, we believe that this is unlikely, since we studied the keratin IFs after releasing the cellular tension that was applied to the filaments (cells were lysed). Thus, it seems likely that only irreversible stretching should be retained in our analysis. Irreversible stretching could be induced by extensive stretching of filaments above 200%, which would result in α-helix to β-sheet transitions of the coiled-coil domains . The 2D classes with very thin diameters and a straight appearance might reflect such irreversible stretched filaments. Since these classes are frequently found in the cellular assembled keratins, this may be physiologically relevant.Tilting seems to be the most likely explanation for the differences in the repeating distance, because we already see in the tomograms that tilted filaments are present in the sample.We added the above to the Discussion section.6) The authors should relate the caveats and/or assumptions associated with the approach they used to "reconstitute" the filaments (lines 227-240). I thought that as actually reconstituted filaments from purified K5 and K14 proteins – including that reference would have been very exciting.We apologize for the misunderstanding. In this study, we only used a computational in silico reconstitution. Namely, we used the 2D class averaging and mapped the classes back to the original position from which the segments originated along the filaments. This approach was developed in Martins et al., 2021. Throughout the entire study we used only cellular assembled K5/K14 filaments and studied them only within ghost cells. We revised the explanation and changed the term into ‘computational reconstitution’.7) The variable sub-architecture of filaments may be a key determinant that underlies the property of self-organization of keratin filaments – the latter has been best characterized, biochemically, in a 2002 MBoC paper by Yamada et al. 2009 J Cell Biol paper by Lee and Coulombe. Upon a modest shift in pH , K5-K14 undergo bundling to a remarkable degree, a property the significantly enhances their micromechanical properties . Please consider discussing.We thank the reviewers for this point. To our knowledge, Lee and Coulombe, 2009 and Yamada et al., 2002, focused on the bundling properties of keratin filaments and the regions involved in inter-filament interactions. This is very interesting and their studies yielded fascinating insights into the self-organizing properties of K5/K14 filaments. In our analysis, we focused on single individual filaments, non-bundled filaments, and applied single particle image processing procedures. Furthermore, the sample preparation procedure involved the removal of soluble parts of the cytoplasm and therefore some changes in the keratin IF network may occur. Since we cannot guarantee that the network organization we observe in our ghost cells is the same as it was in intact cells, we only focused on individual keratin IFs. We have now referred to these articles in the context of keratin meshworks.8) Lines 351-352. Given all the biases that have gone into selection of individual fibers for analysis, I question the rationale for spending so much time discussing persistence length, given that in this regard this current study contributes little to what was already known in that regard.We thank the Reviewer for this comment and agree that the discussion about the persistence length is very long. We have shortened this section.9) The observation of a "central core", if this is real, is a game changer in the field. Could the core density be "just another protofilament" that happens the be centrally located in cross-section? Does this core show a helical pattern along the main axis of the fiber? Is the core present whether the filament are comprised of protofilaments showing a heliocal pattern, or only in filaments for which the protofilaments are "straight? Finally, could the core be related to the end domains?  Here, it is important to recognize that Lars Norlen (J Invest Dermatol 2004) has reported on such a central core in native keratin filaments in cross-section when analyzing terminally differentiated keratinocytes of epidermis using cryoEM analysis of sections prepared from flash-frozen, vitrified skin tissue. His findings should be discussed.The central core density may represent an additional protofilament that is located in the center of the filament. It was found in all the keratin IFs analyzed in this study, regardless of whether they show a straight or a helical pattern. As a control, we calculated a rotationally averaged structure as seen in Figure 4G separately from only helical and only straight 2D classes and both showed a central density. Furthermore, no cross-sectional view could be detected where the filament central core was missing. In the revised manuscript we further analyzed filaments seen in cryo-tomograms , it showed a continuous density within the luminal space. It further supports the idea that the density is of structured domains, rather than the unstructured head or tail domains.Moreover, we recently identified a central luminal density in vimentin filaments, and verified that it cannot be the head or the tail of vimentin . Although major structural differences between keratin and vimentin IFs are apparent, they share some common structural properties.Whether the central density follows a helical symmetry remains unknown. However, due to steric restriction, it is unlikely that it would exhibit the same helical parameters as the tubular keratin scaffold. In the additional analysis that was added to the revised manuscript, we show that the central density is not always located in the exact center of the filament, but can move within the filament tube . These results are presented and discussed in the revised manuscript.We thank the Reviewers for pointing out the studies by Norlen et al. Their findings agree very well with our findings and are discussed in the revised manuscript.10) What about the unstructured end domains at the N- and C-termini of K5 and K14? Any insight about where they may be located? The head domains, in particular, are as "large" in primary structure as are subdomain 1B and coil 2.The flexible head and tail domains were predicted to be intrinsically unstructured. Therefore, it is likely that they would not have a substantial contribution to the densities of the averaged KIF structure. A high-resolution 3D structural analysis would be necessary to answer these questions. Unfortunately, we are not sure we can deduce that information from our vimentin IF structural analysis since they clearly assemble differently and a minor rotation of keratin protofilaments may result in different directions of the N- and C- termini.11) Please comment on how this work compares to two earlier reports in the literature. I.e. the cryo-EM of vimentin filaments , that shows an octameric, i.e. protofibrillar organization of IF, in agreement with the keratin work published by Ueli Aebi (JCB 1983). In the latter paper, a four-stranded helical arrangement of protofibrils is shown. Also, the assembly process via unit-length filaments gives a symmetry of filaments according to their repeat-length of 43 nm, etc.We thank the Reviewer for this comment and have now added a paragraph in the discussion regarding these references.As mentioned above, we see major structural differences between vimentin and keratin IFs. Although some literature proposed the idea of universal 32-mer IFs, which would be the basic building block of all cytoplasmic intermediate filaments, this model never agreed with the experimental evidence. Keratin IFs contain much less mass per length  than vimentin  and therefore fewer monomers in cross-section. Therefore, at this stage we are not confident that vimentin and keratin filaments are similar.Our study supports the notion that IFs do not adhere to a common building plan, but show substantial diversity among the different types .We thank the reviewers for pointing out that the ‘repeat distance’ and of a helix should be clarified, as it might cause confusion with the ‘repeating length’ of a helix, which is not the parameter we measured here. In helical parameter terms, our ‘repeat distance’ refers to the ‘pitch’ of a helix, describing the distance required to complete a 360° helix turn. To clarify the helical parameter we determined with the autocorrelation analysis, we renamed the repeat distance to ‘pitch’, as this represents the correct nomenclature. Our measurements therefore describe different structural features than the 43 nm repeat length of an ULF. It agrees with the helical pitch shown in Aebi et al., 1983, measured by Power spectrum analysis of negatively stained keratin filaments.