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  1. Author Response:

    Reviewer #2:

    Some aspects of the analysis and interpretation of the fluorescence result require clarification:

    1. The propagating patterns in the kymographs of mCFP and mCit (Fig 5BCFG) are puzzling. The authors contributed it to inherent locomotion artifacts, noise and internal sarcomere rearrangement during motion. While some of these may be true, could these be image processing artifacts? The authors stated in the method section that the fluorescence intensity at a particular body segment is obtained by drawing a perpendicular line to the midline. The pixels that it intersects will provide the fluorescence intensity. This approach does not seem to account for the fluorophore density change due to tissue compaction and expansion, resulting in overcounting intensity in the inner circle and undercounting at the outer circle - similar to the observed intensity patterns Fig 5BCFG. Perhaps it would have been helpful if the intensities were normalized by the arclength at the different radii from the center of the curvature.

    We agree that the pure fluorescent intensity changes could in part be due to fluorophores being compacted because tissues are being compacted, as in Fig 5BCFG. However, ratiometric imaging (Fig 5DH) takes this into account since the compacting happens to both the mCFP and the mCitrine signals. This is the main reason that ratiometric imaging is more advantageous. Fig 5DH do show differences between the two strains. On the bottom of page 11 and beginning of page 12, we discuss the ratiometric nature of FRET measurement, and on the second paragraph on page 12, we specifically discuss the differences in the dynamics of the FRET-contraction- relaxation cycle between the strains. We believe both of these points address the concern on optical/image processing artifacts.

    We also note that normalization of either the mCitrine or the mCFP signals are not possible because both of these signals theoretically could change, both due to FRET and due to motion artifacts. In other words, we do not expect either signal to remain constant while the worm is moving around, so it is not possible to normalize.

    1. As related to the previous comment, but more generally, image analysis is a critical and sensitive step towards the interpretation of the fluorescence results. The authors would need to elaborate if and how errors in the image processing might contribute to the emergence of correlation between FRET and curvature. For instance, the CFP and mCit expression levels vary significantly along the body of the worm (Fig 5) and should be time-invariant. If an error in image processing picks up nearby spatial variations as the worm moves, the detected fluorescence will become time-variant and correlate with the worm's motion. It is unclear whether this could this happen with the current algorithm. This is a crucial assessment as it is crucial to ensure the observed small FRET changes (+/- 0.015) are due to molecular stretching and not artifacts of image processing.

    We agree that the expression level of the fluorophore proteins is not uniform along the body positions and also varies from animal to animal, but we would like to clarify that the FRET measurement is self-referenced. More importantly we are not simply looking at the FRET signal strength, but in the strength of the correlation between FRET and curvature in each position locally, which is not intensity-dependent. Furthermore, in the analyses we have performed, we essentially have sampled tens of thousands of points, so errors from image processing would be averaged out. One potential issue the reviewer alluded to is motion-artifact; this is very important, as we have shown in the control strain. Indeed there is motion-induced artifact (e.g. light scattered from the groove in the agar the animal is making). This is the reason we do not just take correlations at face value; both experimental and control groups show correlation, but our data show that the experimental group shows stronger correlation. Our conclusion is thus based on comparisons with controls and takes into account potential sources of error.

    1. The shape and meaning of FRET change in the contraction-relaxation cycles (Fig 7) would require further interpretation. The data shows that the extrema and phase of the FRET signal correlate to curvature, and thereby, sarcomere stretching. It is unclear whether it is valid to assume the stretching or relaxing of sarcomeres apply tension directly over each twitchin. Is the binding-unbinding transition of NL to TwcK two-state? If so, would this lead to two-state behaviour in the observed FRET?

    The force-induced unfolding of TwcK at the molecular level has been studied using AFM (Greene et al, 2008, Biophys J, 95:1360-1370) as well as computationally, applying steered molecular dynamics simulations (von Castelmur et al, 2012, PNAS, 109: 13608-13). Neither AFM data nor simulations revealed defined unfolding features that could be attributed to the NL sequence under those experimental conditions. Thus, we must apply the simplified assumption that the unfolding/refolding of the NL is a one-step process, leading to two states: (1) folded NL- Kin assembly and (2) stretched NL plus kinase. It is very possible that mechanical intermediates of unfolding exist, but these remain unknown and undetected to this date. Equally, it seems rather plausible that unfolding occurs somewhat asynchronously in the sarcomere, where individual molecules might be at different stages of unfolding at the molecular level. In this regard, it is important to notice that - contrary to single molecule methodologies- the FRET signal in this study is an “average” value over a huge number of individual molecules. Thus, the highly averaged nature of the signal does not permit revealing or interpreting fine detail in the folding/unfolding phases. In summary, the "two states" approximation seems to suffice and to be consistent with the fundamental sine wave character of the change in FRET signal.

    1. The reason behind the small observed FRET change (+/-0.015) requires further clarification. Is it because (1) all FRET sensors changed slightly, or (2) a small fraction of FRET sensors changed from high to low FRET.

    We thank the referee for calling our attention to the need of clarifying this point to the reader. The FRET method applied in this study yields an “average” signal, to which a large number of individual molecules contribute. Because of its “average” nature, the signal cannot be attributed to individual changes in individual molecules. Therefore, the two scenarios described by the reviewer are not resolvable in this case. In other words, asynchronous unfolding cannot be studied in this way. To clarify this aspect of the work to the reader, we have added a statement in the Discussion section.

    1. The manuscript provides strong evidence of FRET correlating to curvature during the muscle contraction cycle. However, the causality is less clear. It is unclear whether the contraction force causes the FRET change, or can curvature without any active contraction cause FRET change. For instance, it is unclear whether, if the worm were dead or myosin activity inhibited, the bending of the worm would cause FRET change.

    This is a very interesting question from the reviewer that is well worthy of future investigation. As mentioned in the response to reviewer 1’s comment, we have tried “bending” worms and “freezing” worms in different postures, but that experimentation did not yield detectable or interpretable FRET changes. It is, however, the case that our experimentation was neither directed nor technically designed to establish the mechanistic source of the molecular conformational change in this kinase. The work - on first principle - was directed to reveal whether the hypothesized molecular changes occur in the working muscle context in vivo and, therefore, to test the physiological validity of the partial-unfolding mechanism of kinase regulation. We agree that clarifying the link between such changes and the active/passive mechanics of the sarcomere is a much desirable future pursuit.

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  2. Evaluation Summary:

    This paper will be of interest to mechanobiologists and muscle scientists interested in how contraction of muscle may be linked to mechanical activation of a kinase domain in a large structural protein in a living animal. The study combines imaging of the moving live animal with FRET measurements to detect the structural (and presumably the activation) state of twitchin in C. elegans. The data convincingly shows that this activation is coupled to muscle contraction.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1, Reviewer #2 and Reviewer #3 agreed to share their names with the authors.)

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  3. Reviewer #1 (Public Review):

    Twitchin kinase is a sarcomeric protein found in the muscles of the nematode, C. elegans, whose activity is thought to be mechanically regulated by stretch of the muscle. The authors construct transgenic animals containing a twitchin variant with built in FRET sensors that should report the structural state and, by inference, the activity state of the protein in the muscle as the worm moves in a dish. A control variant is constructed containing the same two FRET pairs, but located in a position of the molecule that should not be sensitive to stretch. They show periodic changes in the FRET signal that correlates with the state of muscle contraction/relaxation.

    A major strength of the study is the technical novelty of combining brightfield imaging of the undulating worms with FRET measurements in real time. Care has been taken to essentially align many events as the worm moves, correcting for motion in order to align the two imaging modalities and to be able to present the data in the form of kymographs. The construction of the stretch-sensitive and control twitchin constructs are based on crystal structures and are logical. The manuscript is well written and possible artifacts are discussed. The results are convincing, but not overstated. The problem is that the study is dealing with a complex living system and signal noise arises from several sources. While a good control was designed that, ideally, should not show any change in FRET signal, there are changes that are in the same "direction" as those seen with the experimental construct. The changes seen with the control however are smaller. Another concern, which is well discussed, is that the constructs for most of the experiments were overexpressed in the worms in order to gain a larger signal and it is not clear now the "extra" molecules are binding within the sarcomere and whether they would be subjected to the same stresses as the fraction that is bound in the spot usually occupied by native twitchin. This is addressed using CRISPR/Cas9 to create a knock-in worm containing the full length FRET-twitchin construct. This worm shows the expected changes, but with a lower signal to noise ratio due to the weaker signal.

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  4. Reviewer #2 (Public Review):

    Porto et al. developed a method to image the force-induced unfolding of twitchin kinase (TwcK) by FRET at the whole organism (C. elegans) level and correlated to its motion. The twitchin kinase contains autoinhibitory domains (NL+CRD) that can be mechanically unwrapped from the kinase, leading to its activation. The authors designed experiments to see whether this mechanically-coupled activation happens or not during the muscle contraction of live C. elegans. To do so, they engineered FRET donors and acceptors (mCFP and mCit) to flanking positions around TwcK. They did so without affecting the auto-inhibitory functions of TwcK. As a control, they flanked a nearby Ig domain with the same FRET pairs. The hypothesis is that under force, the unravelling and stretching of the NL domain from TwcK will lead to FRET decrease. While in the control case, Ig domains can resist mechanical unfolding, and FRET would not change. The authors were able to image the whole organism with NIR-brightfield, mCFP and mCit. Channels simultaneously with reasonable spatial and temporal resolution. Image processing algorithms were developed to correlate the C. elegans motion (curvature along the body of C.elegans) to the fluorescence at corresponding body locations. They found propagating "waves" of curvature from the head to tail of the worm in kymographs of body curvature (as expected) and fluorescence in mCFP, mCit, and FRET channels, which is somewhat unexpected. They found the magnitude of FRET change for the mCit-TwcK-mCFP to be statistically greater than the control mCFP-Ig-mCit, although both exhibited a significant correlation with the worm's body curvature. During the contraction and relaxation cycles of the muscles, the FRET change in the mCit-TwcK-mCFP construct is also greater than that of the control group. The authors contributed the observed FRET changes in mCFP-Ig-mCit to various factors, including imaging and motion artifacts. And therefore, the difference observed between the experiment and control is due to the force-induced unfolding of the NL domain from TwcK. The authors suggested that the force-induced unfolding of autoinhibitory peptide activates the kinase, which may have physiological relevance to be discovered in future studies.

    Strengths:

    1. Traditionally, in vitro characterizations of molecules were performed to infer their biological function, which requires knowledge of their complex physiological environment that may not be available. Direct, in vivo, experimental measurement of mechanically-coupled activation of signalling proteins in this study is crucial to understand their physiologically-relevant function and allows correlation to the function at the organism level. This is a beautiful demonstration relating molecular mechanical events in the context of the system it works in. I also recognize and respect the challenges undertaken by the authors in this research.

    2. The overall idea and design of the experiment are elegant. The authors created a transgenic worm that allowed the FRET to be monitored in vivo over the entire body of the worm while simultaneously tracking its motion. The new methodology developed in this study can be potentially adopted to study other mechanically-activated systems in vivo.

    Some aspects of the analysis and interpretation of the fluorescence result require clarification:

    1. The propagating patterns in the kymographs of mCFP and mCit (Fig 5BCFG) are puzzling. The authors contributed it to inherent locomotion artifacts, noise and internal sarcomere rearrangement during motion. While some of these may be true, could these be image processing artifacts? The authors stated in the method section that the fluorescence intensity at a particular body segment is obtained by drawing a perpendicular line to the midline. The pixels that it intersects will provide the fluorescence intensity. This approach does not seem to account for the fluorophore density change due to tissue compaction and expansion, resulting in overcounting intensity in the inner circle and undercounting at the outer circle - similar to the observed intensity patterns Fig 5BCFG. Perhaps it would have been helpful if the intensities were normalized by the arclength at the different radii from the center of the curvature.

    2. As related to the previous comment, but more generally, image analysis is a critical and sensitive step towards the interpretation of the fluorescence results. The authors would need to elaborate if and how errors in the image processing might contribute to the emergence of correlation between FRET and curvature. For instance, the CFP and mCit expression levels vary significantly along the body of the worm (Fig 5) and should be time-invariant. If an error in image processing picks up nearby spatial variations as the worm moves, the detected fluorescence will become time-variant and correlate with the worm's motion. It is unclear whether this could this happen with the current algorithm. This is a crucial assessment as it is crucial to ensure the observed small FRET changes (+/- 0.015) are due to molecular stretching and not artifacts of image processing.

    3. The shape and meaning of FRET change in the contraction-relaxation cycles (Fig 7) would require further interpretation. The data shows that the extrema and phase of the FRET signal correlate to curvature, and thereby, sarcomere stretching. It is unclear whether it is valid to assume the stretching or relaxing of sarcomeres apply tension directly over each twitchin. Is the binding-unbinding transition of NL to TwcK two-state? If so, would this lead to two-state behaviour in the observed FRET?

    4. The reason behind the small observed FRET change (+/-0.015) requires further clarification. Is it because (1) all FRET sensors changed slightly, or (2) a small fraction of FRET sensors changed from high to low FRET.

    5. The manuscript provides strong evidence of FRET correlating to curvature during the muscle contraction cycle. However, the causality is less clear. It is unclear whether the contraction force causes the FRET change, or can curvature without any active contraction cause FRET change. For instance, it is unclear whether, if the worm were dead or myosin activity inhibited, the bending of the worm would cause FRET change.

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  5. Reviewer #3 (Public Review):

    Porto and colleagues explore the possibility that cytoskeletal protein kinases like twitchin and its vertebrate analogues may play a role in mechanosensing. The cytoskeletal integration of proteins like twitchin, titin or obscurin/unc-89, their established roles in maintaining elastic connections between myofilaments and evidence from single-molecule studies on force-induced conformational changes all suggest that such a role is plausible. However, direct proof in functional sarcomeres that physiological mechanical forces can lead to functionally significant conformational changes in cytoskeletal kinases have so far been missing.

    The authors fill this important gap by using a cell biophysical approach in the transparent nematode C. elegans, employing transgenic and genome-edited animals expressing FRET mechanosensor constructs to explore whether mechanical stress associated with nematode locomotion could induce conformational changes in the twitchin kinase region. The development for this aim of an imaging and image analysis platform that combines information on locomotion with fluorescence output is an important advance in itself.

    This is a technically cutting-edge, interdisciplinary work, employing novel imaging approaches that will pave the way for many other studies on different proteins in the nematode and possible other model organisms. The findings are highly intriguing and could represent ground-breaking work into cytoskeletal signalling mechanisms.

    The data suggest that the twitchin kinase FRET mechanosensor responds to changes in body curvature occurring during locomotion and therefore reports on conformational changes in the kinase region that would be compatible with a mechanically gated activation mechanism.
    The possibility of intra- versus inter-molecular FRET is discussed and addressed but may require further validation.

    The paper is well illustrated and very clearly written and explained.

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