I have a picture in my textbook that is confusing me as to how they are different.I tried looking for some info on the internet, but could'nt get it clear.Please help me.
I will try to help. But, in the future, please post a picture of the confusing diagram to help us help you.
edit: now that I see your diagram, I'm not sure if this answer is helpful. Will re-consider and possibly edit this response. Thanks for including it!
Grana lamellae refer to the lamellae (membranes) in direct contact with photosynthetic stacks (grana), where the stroma lamellae are the ones that are connecting between individual stacks (see here). My understanding is that they are functionally and compositionally very similar, the only difference being the region of the lamellae in question (link to paper, sorry for JSTOR paywall). Check out the Wikipedia page for Chloroplasts for some more diagrams. Maybe one here will help this make more sense to you!
Lecture notes, lectures 7 and 8, Muscle Types, Bone & Cartilage
1 Enquiries and Contact School Medical and Molecular Biosciences Room CB04.06.66C (by appointment ONLY) Phone: 9514 4157 E-mail: [email protected] Subject line MUST start with ‘91500 Histology’
2 Prescribed Text Histology A Text and Atlas 6th ed 2011, Ross MH &ampamp Pawlina W, Lippincott Williams and Wilkins Publ Other useful, replacement atlases which can be purchased second hand, many these will not have sufficient factual information but are good for morphology (tissue structure) Histology and Cell Biology: An Introduction to Pathology 3rd ed. 2012 Kierszenbaum A and Tres T, Mosby Publ. DeFiore’s Atlas of Histology with Functional Correlations, Eroshenko VP, 12 th ed. 2012, Point - / Lippincott, Williams and Wilkins Publ. Atlas of Functional Histology 2nd ed. 2010, Kerr JB, Mosby Publ. (most images come from the 1st ed) Atlas of Histology with Functional and Clinical Correlations 2010, Dongmei C, Daley W, Fratkin JD, Haines DE, Lynch JC, Naftel JP and Yang G, Wolters Kluwer / Lippincott, Williams and Wilkins Publ. Junqueira’s Basic Histology, 12th ed. 2010, Mescher AL, Lange / McGraw Hill Publ. Color Atlas of Histology, 5th ed. 2009, Gartner LP and Hiatt JL, Lippincott, Williams and Wilkins Publ. Netter’s Essential Histology, 2008, Ovalle WK and Nahirney PC, Saunders- Elsevier Publ.
- Know the basic histological features of the three muscle types and be able to describe the key differences.
- Relate the histological features of the three muscle types to their key functions.
- Provide examples of the locations for the three different muscle types.
5 Muscle Histology Types: - Skeletal - Smooth - Cardiac
Skeletal Muscle Sarcolemma
Organization of Skeletal Muscle Ross Kaye &ampamp Pawlina Figure 10.3 - Image
Basic Contractile Unit - Sarcomere Myofibrils
Myofibrils linked in series
Skeletal Muscle Fibre Group of skeletal muscle cells
Nuclei located at periphery of fibre Endomysium Perimysium
Epimysium surrounds the entire muscle
o Large numbers in the postural muscles of the neck, and proportionally back and legs. Type II A Fibres ( fast twitch or fast oxidative) Contain very large amounts of myoglobin, mitochondria and blood capillaries. Type II A fibres are red, have a very high capacity for generating ATP by oxidative metabolic processes, split ATP at a very rapid rate Have a fast contraction velocity and are resistant to fatigue. o Such fibres are infrequently found in humans. Type II B Fibres (fast twitch or fast glycolytic) Contain a low content of myoglobin, few mitochondria, few blood capillaries and large amounts glycogen Type II B fibres are white, geared to generate ATP by anaerobic metabolic processes, not able to supply skeletal muscle fibres continuously with sufficient ATP, fatigue easily, split ATP at a fast rate and have a fast contraction velocity. o Found in large numbers in the muscles of the arms and shoulders.
Body Muscle Make-up – NOT EXAMINABLE Most skeletal muscles of the body are a mixture of all three types o Proportion varies depending on the usual action of the muscle Most skeletal muscle is a mixture of all three types of skeletal o All the skeletal muscle fibres of any one motor unit are all the same Different skeletal muscle fibres depend on need o Activation of various motor units is determined in the brain and
o For a weak contraction only type I fibres are activated by their
o Stronger contraction then motor units of type II A fibres are
o Maximal contraction activates both motor units of type IIA &ampamp II B
Exercise Fibre Type Modification – NOT EXAMINABLE Endurance exercises - running or swimming o Cause a gradual transformation of type II B fibres into type II A fibres o Muscle fibres show a slight increase in diameter, mitochondria,
o Result of cardiovascular and respiratory changes that cause skeletal
Great strength for short periods - weight lifting o Produce an increase in the size and strength of type II B fibres o Due to increased synthesis of thin and thick myofilaments building
Sprint training o Builds the super-fast (IIb) o Can release exercise-induced growth hormone.
- Skeletal Muscle Fibre Characteristics – NOT EXAMINABLE Number of different skeletal muscle fibres does not change o The characteristics of those present can be altered. Adults have ≈ 60% fast muscle fibre &ampamp 40% slow-twitch fibre Fibre Type
1 X5 X
Fibre Type Type I fibres Type II A fibres Type II B fibres
Contraction time Slow Fast Very Fast
Size of motor neuron Small Large Very Large
Resistance to fatigue High Intermediate Low
Activity Used for Aerobic Long term anaerobic
Force production Low High Very High
Mitochondrial density High High Low
Capillary density High Intermediate Low
Oxidative capacity High High Low
Glycolytic capacity Low High High
Major storage fuel Triglyceri des CP, Glycogen CP, Glycogen
Smooth Muscle Individual cells with central nuclei Small size Non-striated, but contain actin &ampamp myosin which criss-cross the cytoplasm (not around the nucleus)
Sparsely innervated by autonomic system o Both parasympathetic &ampamp sympathetic components
Regeneration of Smooth Muscle Retain regenerative capacity So can proliferate and regenerate lost smooth muscle
Smooth Muscle Cells LP Kerr Figure 5.17a - Image
Smooth Muscle Cells HP Kerr Figure 5.17c - Image
EM. Smooth Muscle Cells Kerr Figure 5.18a - Image
EM. Smooth Muscle Cells Dense Bodies Kerr Figure 5.18b- Image
Diagram Smooth Muscle Cell Contraction - Image http://www.cytochemistry.net/microanatomy/muscle/ smooth_muscle_2001.htm
Smooth Muscle Locations Veins &ampamp Arteries Lungs Gut Gall &ampamp Urinary Bladders Uterus Ureter &ampamp Fallopian Tube Fibromuscular stroma of the Prostate
Smooth Muscle of Gut Kerr Figure 13.24 - Image
Smooth Muscle of Gut HP Plastic section Kerr Figure 5.17d – Image
Smooth Muscle of Trachea Kerr Figure 11.4 c- Image
Smooth Muscle of Muscular Artery Kerr Figure 7.8b Image
Smooth Muscle of Prostatic Stroma Kerr Figure 18.20b- Image
- Visual Summary of All Muscle Types - Diagram – Figure 11.1 Basic Histology 4th Ed Junqueira LC &ampamp &ampamp Carneiro J, Lange Publ 1983
Histology of Cartilage and Bone
Describe the structure, chemical composition and functional differences of compact and woven bone.
List the structural differences of the 3 types of cartilage.
Be able to describe bone development in the epiphyseal growth plate.
Differentiate the matrix structure and functional importance of bone and cartilage matrices.
Name the 3 types of joints and describe the synovial joint structure and function.
Also Known As Connective Tissues Bone Cartilage Joints
Head of Femur XS Kerr fig 9.10a - image
Types of Bone Lamellar Bone (80% skeletal weight) o Also known as Cortical, Compact, or Dense bone o Weight bearing tissue of long bones o Mature Woven Bone o Also known as Cancellous, Trabecular or Spongy bone o Supportive, scaffolding structure of inner bone o In healing bone is the immature precursor
Cancellous compared to Compact bone Ross, Kaye and Pawlina fig
Bone Cellular Composition Osteoprogenitor cell o Known as bone lining cells of peri- and end-osteums o Mesenchymal in origin, are fibroblast-like (fibroblastoid) Osteoblast o Bone forming cells o Regulate bone mineralization Osteocytes o Quiescent cells that regulate serum calcium &ampamp phosphate Osteoclasts o Macrophage/remodeller o Produce collagenases
Periosteum and Bone Spicules Kerr fig 9.4b – image
EM of Osteocytes bone growth layer Ross, Kaye and Pawlina fig 8.
Osteons remodelling Kerr fig 9.5a - image
Osteon system branching Kerr fig 9.5c - image
Osteon of Lamellar Bone Layered cylinders of collagen Lacunae of osteocytes between each layer (or lamellum) Canaliculae radiate from each lacuna and house osteocyte cellular processes Central - Haversian canal contains neurovascular components
Ground bone: osteons and lacunae Kerr fig 9.3a - image
Ground bone Polarized light highlighting collagen Kerr fig 9.2b - image
Osteocytes in lacunae with fine communication channels Kerr fig
Interlacunar channels Kerr fig 9.3d - image
Woven Bone Within core of long bones Collagen runs in various directions Oriented to mechanical loads &ampamp stresses acting on the bone Lined by osteoblasts
Head of long bone Kerr fig 9.2a - image
Head of long bone Kerr fig 9.4a - image
Spongy bone Kerr fig 9.10b - image
Cartilage Does not regenerate Is avascular (no blood supply) Nutrients by diffusion from perichondrium &ampamp synovial fluid Form the bone growth plate o Known as the epiphyseal plate
Cartilage of Developing Bone, first sign of ossification is the formation of blood vessels Kerr fig 9.8d - image
Cartilage Mineralization at the Epiphyseal Plate Kerr fig 9.11a - image
Endochondral Bone Growth Kerr fig 9.8e- image
The Epiphyseal Growth Plate Kerr fig 9.10a - image
Cartilage function Frictionless surface for smooth movement Shock absorption Resists mechanical stress
Cartilage Structure - Cells Cells o Chondroblasts
The bone and cartilage interface Kerr fig 9.16 - image
Cartilage growth Kerr fig 9.11d - image
Cartilage Structure - Matrix Matrix (gel-like) Glycosaminoglycans (GAGs) Hyaluronic acid, chondroitin &ampamp keratan sulphates which aggregated with collagen fibrils Proteoglycans Collagen Hydrated (between 60 to 78% water) bound to negatively charged GAGs
Chemistry of cartilage Basic Concepts in Cell Biology &ampamp Histology 2000 JC McKenzie &ampamp RM Klein, McGraw-Hill Publ. Figure 14.1 - image
Metastasis remains the greatest challenge in the clinical management of cancer. Cell motility is a fundamental and ancient cellular behaviour that contributes to metastasis and is conserved in simple organisms. In this Review, we evaluate insights relevant to human cancer that are derived from the study of cell motility in non-mammalian model organisms. Dictyostelium discoideum, Caenorhabditis elegans, Drosophila melanogaster and Danio rerio permit direct observation of cells moving in complex native environments and lend themselves to large-scale genetic and pharmacological screening. We highlight insights derived from each of these organisms, including the detailed signalling network that governs chemotaxis towards chemokines a novel mechanism of basement membrane invasion the positive role of E-cadherin in collective direction-sensing the identification and optimization of kinase inhibitors for metastatic thyroid cancer on the basis of work in flies and the value of zebrafish for live imaging, especially of vascular remodelling and interactions between tumour cells and host tissues. While the motility of tumour cells and certain host cells promotes metastatic spread, the motility of tumour-reactive T cells likely increases their antitumour effects. Therefore, it is important to elucidate the mechanisms underlying all types of cell motility, with the ultimate goal of identifying combination therapies that will increase the motility of beneficial cells and block the spread of harmful cells.
Dynamic localization of myosin
Using confocal microscopy, we observed border cell migration live and at high spatio-temporal resolution during delamination (Figure 1 Supplemental Movie S1). The first morphological changes after border cell fate specification are that the cluster rounds up and multiple cells extend and retract actin-rich protrusions for ∼1 h (Figure 1, D–F). Eventually a single leader cell with a dominant forward protrusion emerges (Figure 1G). As the lead cell moves forward, additional cells delaminate from the epithelium (Figure 1H), ultimately detaching from the epithelial cells that remain behind (Figure 1I).
Since myosin II assembles cooperatively on contractile filaments, accumulating to its highest levels at sites where it is active (Uehara et al., 2010), we examined its localization together with F-actin during border cell migration. We used a fluorescently tagged form of myosin light chain, known in Drosophila as Spaghetti squash (Sqh). The Sqh-mCherry fusion protein is expressed under the endogenous genomic regulatory sequences and is fully functional (Martin et al., 2009). Like E-cad (Cai et al., 2014), Sqh-mCherry accumulates to higher levels in somatic cells than in the germline (Figure 2, A–D) even though the germline contains high levels of F-actin (Figure 2, A and B). The Sqh-mCherry protein is present in border cells throughout their migration and is enriched near the apical surfaces of all follicle cells (Figure 2, A–D) including polar cells (Figure 2E). A similar pattern is observed with a Sqh-GFP and Sqh-TS::GFP (Supplemental Figure S1), although the apical polar cell labeling is more prominent with the mCherry fusion. Knockdown of Sqh by RNAi in polar cells does not result in a detectable phenotype (Majumder et al., 2012), but the Sqh accumulation serves as a useful marker of polar cell position and the apical side of the cluster.
FIGURE 2: Spaghetti squash (sqh) distribution during border cell migration. (A–D) Maximum intensity projections of fixed egg chambers at stages 9 (A, C) and 10 (B, D) labeled with phalloidin for F-actin (green), Hoechst (blue), and expressing Sqh-mCherry expressed from its endogenous promoter and stained using an anti-mCherry antibody. Arrow indicates border cell position and arrowhead indicates apical surfaces of posterior follicle cells (C). (E–M) High-magnification maximum intensity projections of Sqh-mCherry localization during delamination (E, H, K), mid migration (F, I, L), and at the completion of migration (G, J, M). White arrows indicate the accumulation of Sqh-mCherry at the base of protrusions (E), at the cluster periphery (F), and the polar cell (p) apical surfaces facing the oocyte after docking at stage 10 (G). Scale bars in A–D and E-M are same. All scale bars are 20 µm.
In fixed images of outer, migratory border cells, the pattern of Sqh-mCherry only partially overlaps with F-actin (Figure 2, H–M). The Sqh-mCherry pattern is not identical from one cluster to the other, suggesting it is dynamic. We noted prominent accumulation of Sqh-mCherry at the base of protrusions (Figure 2, E and K). In addition, patches of Sqh-mCherry are evident at the periphery of some clusters during migration (Figure 2, F and L), consistent with a previous report of dynamic Sqh flashes during migration (Aranjuez et al., 2016). At the end of migration, myosin accumulates apically in the cluster at the border cell/oocyte interface (Figure 2, G and M).
To determine to what extent myosin colocalizes with E-cad in migrating border cells, we labeled Sqh-mCherry–expressing clusters with anti–E-cad antibody and imaged them using confocal microscopy. E-cad and Sqh-mCherry colocalized extensively (Figure 3, A–C). Furthermore, Airyscan imaging of fixed samples with amplified GFP and mCherry signals at high lateral and axial resolution revealed a high degree of E-cad and Sqh colocalization at cell–cell junctions within the border cell cluster and the apical surfaces of polar cells (Figure 3, D–I Supplemental Figure S2).
FIGURE 3: Colocalization of Sqh and E-cad during border cell migration. Maximum intensity projections of fixed egg chamber expressing Sqh-mCherry at endogenous levels (labeled by mCherry in magenta) and labeled for E-cad (green) (A–C). (D–I) High-magnification views of single Airyscan slices of fixed border cell clusters at junctional (D–F) and apical (G–I) planes. White arrows mark border cell-border cell junctions. D represents the overlay of E and F. G represents the overlay of H and I. Maximum intensity projections of time-lapse imaging for (J, K) Sqh-mCherry and (M, N) E-cad-GFP. Cell junctions (white arrows) and polar cells (p) are represented. Yellow lines indicate the region used to generate the corresponding kymographs for the duration of movies shown in L and O. Scale bars in A–C, D–I, J and K, M and N, and L, O are same. Scale bars are 20 µm (A–N) and 5 µm (L–O).
To compare their dynamics we took z-stacks of Sqh and E-cad for 8 min (Supplemental Movies 2 and 3). To limit phototoxicity, low laser intensities were used, so only the brightest pools of myosin and E-cad were detected (Figure 3, J, K, M, and N). Kymographs from representative clusters show junctional Sqh-mCherry puncta that appear and disappear with a half-life of 30 s (Figure 3L), whereas E-cad is stable for at least 20 min (Figure 3O and unpublished data). Thus, live imaging revealed myosin to be more dynamic than E-cad.
Requirement for myosin II in cell–cell communication
Since Sqh and E-cad colocalize, and E-cad is proposed to mechanically couple border cells, we tested whether myosin also contributes to mechanical coupling. To test the hypothesis that myosin activity mechanically couples lead cells to followers, we inhibited myosin expression or activity in three different ways (Figure 4, A–E). First, we knocked down expression of the light chain using RNAi (Figure 4B). Second, we expressed a nonphosphorylatable form of the light chain (Figure 4C), which likely acts as a dominant-negative (Jordan and Karess, 1997). Finally, we blocked expression of the myosin heavy chain, known as Zipper (Zip) using RNAi (Figure 4D). Each of these manipulations resulted in a significant fraction of clusters displaying multiple ectopic protrusions (Figure 4E). If myosin-mediated contractility couples the lead cells to the followers, then we would expect that wild-type follower cells in contact with a Sqh-deficient leader would exhibit excess protrusions. To test this, we generated border cell clusters composed of a mixture of wild-type and Sqh RNAi–expressing cells (Figure 4, F–L). Wild-type follower cells indeed exhibited excess protrusions when in contact with Sqh-depleted lead cells (Figure 4, G and L Supplemental Figure S3 Supplemental Movies S4 and S5). Live imaging of clusters with reduced Sqh showed an overall higher frequency of ectopic side protrusions that are longer lived than those observed in wild-type controls (Supplemental Figure S4 Supplemental Movies S6–S8).
FIGURE 4: Myosin is required for cell communication. (A–D) Fixed imaging of egg chambers stained for c306-Gal4 tub-GAL80ts driving UAS-Lifeact-GFP together with the indicated UAS-transgenes. (E) Box plots of ectopic protrusions in clusters from A–D (n) represents the total number of clusters counted from at least three independent crosses. Nonautonomous effect of Sqh knockdown on protrusion formation in (F, H, K) control and (G, I, L) sqh-RNAi flip-out clones. Clonal region is marked by anti-GFP antibody (H, I) to show autonomous protrusions. Nonautonomous protrusions are shown by F-actin phalloidin staining (white arrows, G, L). (J) Quantification of nonautonomous ectopic protrusions. The y-axis indicates percentage of clusters with protrusions in GFP-negative cells n = the number of border cell clusters counted. Statistics represents unpaired t test ***p < 0.001, **p < 0.01, *p < 0.05. Scale bars in A–D and F–L are the same. All scale bars are 20 µm.
Normally, protrusions from the lead cell (the cell closest to the oocyte) are longer and longer-lived than protrusions from other cells of the cluster (Prasad and Montell, 2007). The small GTPase Rac is essential for border cell protrusion and migration (Murphy and Montell, 1996), and its activity is highest in protruding cells (Wang et al., 2010). Moreover, focal stimulation of a photoactivatable form of Rac (PA-Rac) in one cell is sufficient to steer the entire cluster (Wang et al., 2010). PA-Rac in the lead cell accelerates forward-directed movement, whereas Rac activation in the rear cell reverses the direction of cluster movement (Wang et al., 2010) (Figure 5, A and B). In both cases, Rac activation in one cell stimulates protrusion in the activated cell and inhibits protrusion of other cells (Wang et al., 2010) (Figure 5, A and B). Thus, the protruding cell steers the whole cluster. E-cad is essential for this cell–cell communication (Cai et al., 2014). To test the hypothesis that myosin is similarly required, we expressed PA-Rac together with sqh RNAi and photoactivated Rac in the rear cell. Protrusions were defined and quantified as previously described (Wang et al., 2018). Inhibition of Sqh resulted in multiple protrusions, not only in the stimulated cell but also from other cells (Figure 5, C–E). We conclude that the protruding cell inhibits protrusion in following cells in a myosin II-dependent manner. Results were similar for clusters imaged near the beginning of their migration (Figure 5, C–E) or near the end (Supplemental Figure S5).
FIGURE 5: Myosin is required for distribution of Rac activity in border cell clusters. (A–D) Live imaging of PA-Rac in slbo-Gal4 control (A, B) or UAS-sqh RNAi–expressing (C, D) clusters. (A ,C) White circle indicates the illuminated region. (B, D) Cluster positions and morphology were marked using mCherry signal in PA-Rac containing flies before (magenta) and after (green) 30 min of photoactivation. White arrows indicate ectopic protrusions. (E) Total number of protrusions observed per cluster for each genotype. Similar results were observed whether clusters were observed near the beginning of migration (Anterior) or near the end (Posterior) (n) indicates the number of clusters evaluated. (F–L) Ratiometric imaging of slbo-Gal4 driving UAS-Rac FRET. Examples of protrusive (F, H, K) or nonprotrusive (G, I, L) clusters are shown. Control clusters expressed UAS-white RNAi. Polar cells (p) do not express slbo-Gal4. (J) Front/back ratio of measured FRET signals for the indicated genotypes in protrusive and nonprotrusive clusters (n) indicates the number of clusters imaged. Scale bars in A–D and F–L are same. All scale bars are 20 µm. All data were analyzed by one-way ANOVA with Tukey Kramer post hoc analysis. ****p < 0.0001, ***p < 0.001, **p < 0.01.
To investigate the mechanism of this myosin-mediated protrusion restriction, we evaluated the effects of altering myosin expression or activity on the pattern of Rac activation in border cell clusters (Figure 5, F–L). In wild-type clusters, Rac activity is highest in protrusions (Wang et al., 2010), specifically while they are extending. Lead cell protrusions typically show the highest Rac activity (Figure 5F), whereas nonprotruding clusters do not exhibit higher Rac activity in the lead cell (Figure 5G). To test the effect of myosin on the distribution of Rac activity, we expressed the established Rac FRET probe in border cells together with sqh RNAi. Sqh RNAi–expressing clusters showed reduced front enrichment of Rac activity relative to control clusters (Figure 5, H and J). Thus, myosin activity is essential for the asymmetry in Rac activation observed in protruding clusters. Expression of a phosphomimetic version of Sqh (SqhE20E21), designed to cause constitutive activation (Hannaford et al., 2018), had a similar effect (Figure 5, J–L), showing that spatial and/or temporal regulation of myosin activity is essential to establish asymmetric Rac activity.
Myosin distribution depends on E-cad
Since myosin and E-cad colocalize and function in cell–cell communication, we asked whether myosin is recruited in an E-cad–dependent manner. We compared the distribution of Sqh-mCherry in control clusters to those with reduced E-cad expression (Figure 6, A–H). Multiple validated RNAi lines that have varying potencies are available for E-cad (Supplemental Table S1). Since border cells with complete E-cad knockdown rarely migrate (Niewiadomska et al., 1999 Cai et al., 2014), we carried out experiments at low temperature (18°C) that produces a mild migration defect to analyze the effect on myosin. Although this approach risks underestimating the phenotypic effect, we thought it was important to compare migratory control and knockdown clusters rather than compare migratory control clusters to immobile E-cad knockdown clusters. Upon partial E-cad knockdown, we observed both protrusive clusters and rounded clusters, as in controls (Figure 6, A–H Supplemental Movies S9–S14). Clusters of both morphologies exhibited significantly reduced cortical myosin compared with controls (Figure 6I). To quantify the effect, we used laser scanning confocal imaging to capture time-lapse movies of migrating border cells labeled with Lifeact-GFP and Sqh-mCherry. Using Imaris image analysis software, we segmented the border cell cluster based on the Lifeact-GFP channel and then isolated the cluster perimeter (Supplemental Movie S15). We used the Sqh-mCherry channel to measure cortical myosin levels normalized to the Sqh-mCherry signal in the nurse cells adjacent to the border cell cluster, to correct for photobleaching. Owing to the normal dynamic fluctuations of cortical myosin, there is great variation in the cortical myosin intensity in wild-type clusters (Figure 6I). E-cad knockdown reduced the overall levels and fluctuations of cortical myosin (Figure 6I). Figure 6J illustrates schematically the effects of low versus high cortical myosin both in control and E-cad knockdown clusters. Together these results show that recruitment of myosin requires E-cad–mediated adhesion between border cells.
FIGURE 6: Mutual requirement for E-cad and Sqh. (A–H) Stills from time-lapse imaging of clusters coexpressing Lifeact-GFP under the control of the slbo enhancer and Sqh-mCherry from its endogenous promoter. (A–D) Control clusters expressing UAS-white RNAi in protrusive (A, B) and round (C, D) clusters. (E–H) Border cells expressing UAS-E-cad RNAi in protrusive (E, F) and round (G, H) clusters. All genotypes include c306-Gal4 and were incubated at 18°C. (B, D, F, H) Myosin-only channel. (I) Box plot comparing the average cortical myosin intensity in control vs. E-cad RNAi–expressing clusters. n refers to the total number of frames measured from six control and nine E-cad RNAi time-lapse movies. (J) Schematic representation of the effects of varying the level of myosin in both protrusive and round clusters. (K–N) Flipout-Gal4–expressing cells (labeled by GFP antibody in green) in clusters expressing control, UAS-white RNAi (K, L), or UAS-sqh RNAi (M, N) stained for E-cad (magenta). Arrow indicates a discontinuity in the junction as observed in the indicated fraction of clonal clusters. Scale bars in A–H and K–N are the same. All scale bars are 20 µm. Data were analyzed using unpaired t test. ****p < 0.0001.
To assess whether myosin also exerts an effect on E-cad and/or cell–cell contacts, we compared the localization of E-cad in control and sqh RNAi–expressing border cells (Figure 6, K–N). We used the FLPout technique (see Materials and Methods) so clusters were composed of a mixture of GFP-positive and GFP-negative cells. In control clusters in which both GFP+ and GFP– cells express normal levels of Sqh, E-cad labeling of the apical polar cell domain and border cell/border cell contacts are evident (Figure 6, K and L). In clusters in which the GFP+ cells also express sqh RNAi, border cell/border cell contacts appeared irregular in 8/36 samples examined (Figure 6, M and N) compared with the relatively smooth contacts between control cells in 29/29 clusters (Figure 6, K and L). The remaining 28 sqh RNAi samples were not clearly distinguishable from wild type. These results suggest that there is normally actomyosin-mediated tension maintaining border cell-border cell contacts, as in epithelial monolayers in vitro (Warner and Longmore, 2009 Acharya et al., 2018 Charras and Yap, 2018).
Myosin functions in retraction of lead protrusions
We noted prominent but transient accumulation of Sqh-mCherry at the base of protrusions (Figures 2E and 7A Supplemental Movies S16 and S17), which has not previously been described. We carried out live imaging and found that, as protrusions approach their maximal extension, Sqh-mCherry accumulates and is followed by protrusion retraction. To quantify this effect, we measured the change in protrusion length (ΔL) per unit time (Figure 7B). Positive ΔL indicates protrusion while negative values of ΔL represent retraction. Plotting myosin intensity as a function of the rate of change of protrusion length demonstrates a positive correlation between myosin accumulation and retraction and a negative correlation with protrusion (Figure 7C).
FIGURE 7: Myosin accumulation precedes protrusion retractions. (A) Stills from time-lapse imaging of a representative cluster expressing Lifeact-GFP (green) and Sqh-mCherry (magenta) during one protrusion extension and retraction cycle. Polar cells are marked with p. (B) Schematic showing how changes in lead cell protrusion lengths (ΔL) were measured. (C) Plot of ΔL vs. myosin intensity in 29 protrusion/retraction cycles from three independent time-lapse movies. All scale bars are 20 µm. R 2 value of the trendline is 0.64. (D) Box plot of instantaneous speed from (77) protrusion and (72) retractions cycles.
This observation forces a reevaluation of the functions of protrusions. On the basis solely of imaging fixed tissue, Fulga and Rørth (2002) suggested that protrusions function as a grapple to pull the cluster forward (Schober and Perrimon, 2002). However such a model implies that the tip of the protrusion adheres strongly to the substrate and would not retract but rather would be subsumed into the advancing cluster. We observed that 130/162 protrusions retracted, suggesting that most protrusions are not effective grapples. The grapple and pull model further predicts that clusters will advance most rapidly when protrusions are maximally extended and that nonprotruding clusters will not advance. We quantified cluster migration speed in relation to protrusion extension and retraction. Importantly, we measured migration speed by following the displacement of the polar cells, rather than following the geometric center of the cluster. This approach is key because the mere extension of a forward-directed protrusion creates an illusion of forward cluster movement when measuring the geometric center, whereas following polar cells does not suffer from this artifact. We found that protruding and retracting clusters move with similar velocities (Figure 7D). Therefore we conclude that protrusions are dynamic and serve some function other than pulling the cluster forward (see Discussion).
Phosphomimetic myosin is sufficient to cause a mesenchymal to amoeboid transition in vivo
Tumor cell lines can undergo a transition from mesenchymal to amoeboid migration both in vitro and when xenografted in mice (Pinner and Sahai, 2008 Friedl and Wolf, 2010 Sanz-Moreno et al., 2011). The mesenchymal mode of motility is characterized by high Rac activity and pseudopod-driven movements, similar to normal border cell migration. In contrast, cells that migrate in an amoeboid manner are round and exhibit blebs due to high Rho and Rho kinase activity. Hyperactivation of Rho is sufficient to drive the mesenchymal to amoeboid transition in some cell lines (Panková et al., 2010 Yilmaz and Christofori, 2010). Amoeboid movement is likely dependent on high actomyosin contractility downstream of Rho, however it is unknown whether hyperactivating myosin is sufficient to trigger a mesenchymal to amoeboid transition. Moreover, to our knowledge such transitions have not been reported in untransformed cells.
To test whether constitutive activation of myosin would cause a similar effect, we expressed the phosphomimetic form of Sqh, SqhE20E21. The substitution of glutamate for serine or threonine at these residues mimics the activation by phosphorylation by myosin light chain kinase. We found that SqhE20E2, like active Rho, is sufficient to cause a transition from collective, pseudopod-dependent border cell migration to amoeboid, blebbing motility (Figure 8 Supplemental Movies S6 and S18–S20). Live imaging of SqhE20E21-expressing clusters revealed that in some frames, some cells exhibited small protrusions (Figure 8E and Supplemental Movie S19). This resulted in migration that was slower than control clusters (Figure 8, D and I). Notably, blebbing-based amoeboid motion in SqhE20E21 clusters is faster than protrusive motility (Figure 8, F and I). Even after reaching the oocyte border, cells expressing SqhE20E21 maintain a rounded, blebbing morphology compared with the epithelial morphology of control clusters (Figure 8, G and H). The transition to amoeboid morphology and migration also caused clusters to break into single cells and cell pairs. This suggests that hyperactive actomyosin contractility is sufficient to break the cell–cell adhesions that normally hold the cluster together. Although sqhE20E21 surprisingly displays reduced motor activity in vitro (Vasquez et al., 2016), we observed similar cluster morphology and blebs when we expressed a constitutively active (CA) version of Rho (Rho1V14) in border cells. Thus SqhE20E21 phenocopies hyperactivation of Rho, suggesting that in vivo SqhE20E21 is constitutively active, as expected (Supplemental Movies S21–S22). We conclude that regulation of the level of myosin activity is important because either reducing or increasing activity impaired border cell migration.
FIGURE 8: Myosin activation causes hypercontractility and membrane blebs. (A–C) Fixed imaging of clusters expressing c306-Gal4 tub-GAL80ts driving UAS-Lifeact-GFP and UAS-white RNAi in control (A), or clusters expressing constitutively active Sqh (B, C). Egg chambers are stained with anti-GFP antibody (green), F-actin (magenta), and Hoechst (blue). Clusters can split and migrate as blebbing amoeboid cells (B) or split into blebbing amoeboid cells that fail to migrate (C). (D–H) High-magnification views of the indicated genotypes in protrusive or blebbing states. Arrows indicate protrusions or membrane blebs in E, F, and H. (I) Box plot of border cell cluster migration speed measured in 10 time-lapses for control and SqhE20E21 expressing clusters in protrusive or bleb phases. Scale bars in A–C and D–H are the same. All scale bars are 20 µm. All data were analyzed by one-way ANOVA with Tukey Kramer post hoc analysis. ***p < 0.001, *p < 0.05.
tissue that makes up stems:
Epidermis the outer layer of the stem - role is protection of cells beneath it , secretes cutin a waxy substance which helps prevent water loss some contain hairs which can be stiff for protection or loaded with irritant chemicals
Parenchyma - packing tissue, parenchyma is most common, unspecialised cells which can be modified e.g into collenchyma and sclerenchyma.
collenchyma gives the tissue its strength found around the outside of the stem just under the epidermis give support but remain living ( not lignin)
sclerenchyma develops as plant gets bigger and needs more support makes strong secondary cell walls lignin is depsited on the cell walls making it no longer permiable the cell dies and becomes hollow forming wood. when it becomes compleatly impregnated it forms a sclereids.
in order from inside nucleus, vacuole, cytoplasm, middle lamellum, parenchyma (primary cell wall) collenchyma (extra cellulose), sclerenchyma (secondary cell wall, with lignin), epidermis.
The physical properties of the extracellular matrix (ECM) milieu are widely acknowledged as fundamental determinants of cell fate, tissue homeostasis, immune response, wound healing, and cancer progression [, , , ]. Within a given tissue, the ECM not only provides structural support but regulates cell signaling via reciprocal biochemical and biophysical cues . On one hand, the ECM contributes to overall tissue mechanics, and the effects of mechanical properties on cell fate and phenotype have been extensively studied using in vitro and in vivo assays [, , , , , , , , , ]. For example, tissues become progressively stiffer as a function of malignant transformation from normal to tumors . In addition, the architecture of the ECM provides structural feedback, such as topographical cues [, , , ]. Topography, simply described, refers to the shape and profile of a given material's surface [, , ]. Cells respond to topographical and stiffness-mediated cues through biochemical signaling via cellular adhesions and cytoskeletal attachments to the ECM . Cell sensing of architectural and mechanical cues is a complex phenomenon where ECM adhesion molecules act concomitantly with intracellular machinery to drive cellular responses . In vivo, tissue topographical cues are heterogeneous, with hybrid structures comprised of aligned ridges and pores that span lengths from nanoscale to microscale [, , ]. On the nanoscale level, ECM proteins can adopt different morphologies, such as globular and fibrillar architectures [17,18]. One such example is fibronectin (FN), which presents different cell binding sites and is alternatively spliced to generate conformation which initiate distinct signaling cascades [22,23]. On the other hand, the chemical specificity of these building blocks in turn also regulate unique signaling cascades. For example, cells that interact with fibronectin fibrils receive distinct chemical cues from those received when exposed to cues derived from collagen type I fibrils. Yet, in some cases, physical cues may dominate cellular response in the presence of a chemical cue. Simulations of stretching of a module of a FN fibril, FN III, is sufficient to override beta one-dependent modulation of increased ligand binding and associated down-stream signaling. Thus, understanding how cells “sense” these interconnected cues and how they influence eventual cell fate remains a perplexing issue.
These concepts are often difficult to discern using naturally derived 3D tissue mimetics, as precise control of ligand density and architecture are often intertwined. Moreover, dissecting differential physical cues such as mechanics from architecture is also challenging. While studies using patterned two-dimensional substrates [24,25] and microfabricated environments  have revealed aspects of cell response to topography, reactions to topographic cues in more physiologically relevant three-dimensional environments are not as well understood. Importantly, three-dimensional cues are likely vital to recapitulate some aspects of physiological mechanosensing. Also, cell attachments to matrices in 3D environments often differ with respect to that observed for cells cultured in 2D substrates, which in turn may impact mechanosensing in specific 3D ECMs. In tissue, 3D topographies consist of highly oriented structures that are not well-recapitulated by in vitro hydrogel models. For example, commonly used collagen hydrogels form fibers that are randomly oriented unless some external micropatterning is imposed during their polymerization . Similarly, laminin-rich ECMs (Matrigel) form amorphous gels devoid of cell-scale structures . To address the need for reproducible 3D culture systems with well-defined matrix architecture and ECM protein composition, we recently developed a method whereby functionalized paramagnetic colloidal particles are magnetically aligned in 3D hydrogels to create fibrils that span microns in length and 10s of nms in widths [17,29]. Fiber alignment, diameter, spacing, and extracellular matrix conjugation to the colloidal particles can be controlled to create defined topography independently of the ligand used to coat the particles. In 3D Matrigel matrices containing aligned particles, mouse fibroblasts and neural cell lines send out protrusions that are longer than those seen in matrices lacking particle alignment, independently of the ECM ligand conjugated to the colloidal particles. When the particles are coated in fibronectin, these cells preferentially extend protrusions either parallel or perpendicular to the fibers. This system allows us to test if cells cultured in matrices where fibrils of the same size and arranged in similar geometries will show similar behavior for different types of ECM proteins. In this system, the bulk mechanical properties were similar regardless of the presence of aligned or unaligned colloidal particles. However, lack of understanding of mechanical cues at the cellular scale, of how ECM nanoparticle conjugation affects cell response, and of mechanistic factors driving cell response to topography limited the use of this system.
Here, we used our system to discern the role of aligned topographical cues, presented across a range of human ECM proteins, on human cell response in Matrigel (laminin-rich) matrices with well-characterized physical properties. Using optical trap-based active microrheology, we measured the 3D microscale viscoelasticity. We then asked how topographical and micromechanical cues influence human normal (human foreskin fibroblast, HFF) and cancer (U87 glioblastoma) cells on this length scale. Using genetic manipulation and small molecule inhibitors, we determined that β1integrin knockdown and fascin inhibition reduced the length of cell protrusions in response to physical cues resulting from fiber alignment in these engineered Matrigel matrices. However, protrusions were still aligned with the fibrils. In contrast, reduced myosin II activity did not affect protrusion length, but protrusions were randomly oriented. We confirmed that myosin II is also required by cells to sense topographical alignment in vivo using the zebrafish brain vasculature as our model system. Our results suggest that normal and cancer cells use similar machinery to respond to the topographical and micromechanical cues in this system, where myosin II may regulate how cells sense topographical cues.