View
8
Download
0
Category
Preview:
Citation preview
1
Postnatal mechanical loading drives adaptation of tissues primarily through modulation 1
of the non-collagenous matrix 2
3
D. E. Zamboulis1*, C. T. Thorpe2, Y. Ashraf Kharaz1, H. L. Birch3, H. R. C. Screen4†, P. D. 4
Clegg1† 5
* Corresponding author: Zamboulis, † Joint last authorship: Screen, Clegg 6
7
1Institute of Ageing and Chronic Disease, Faculty of Health and Life Sciences, University of 8
Liverpool, Liverpool, L7 8TX, United Kingdom 9
2Comparative Biomedical Sciences, The Royal Veterinary College, Royal College Street, 10
London, NW1 0TU, United Kingdom 11
3University College London, Department of Orthopaedics and Musculoskeletal Science, 12
Stanmore Campus, Royal National Orthopaedic Hospital, Stanmore, HA7 4LP, United 13
Kingdom 14
4Institute of Bioengineering, School of Engineering and Materials Science, Queen Mary 15
University of London, London, E1 4NS, United Kingdom 16
17
Abstract 18
Mature connective tissues demonstrate highly specialised properties, remarkably adapted to 19
meet their functional requirements. Tissue adaptation to environmental cues can occur 20
throughout life and poor adaptation commonly results in injury. However, the temporal 21
nature and drivers of functional adaptation remain undefined. Here, we explore functional 22
adaptation and specialisation of mechanically loaded tissues using tendon; a simple aligned 23
biological composite, in which the collagen (fibre phase) and surrounding predominantly 24
non-collagenous matrix (matrix phase) can be interrogated independently. Using an equine 25
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
2
model of late development, we report the first phase-specific analysis of biomechanical, 26
structural and compositional changes seen in functional adaptation, demonstrating adaptation 27
occurs postnatally, following mechanical loading, and is almost exclusively localised to the 28
non-collagenous matrix phase. These novel data redefine adaptation in connective tissue, 29
highlighting the fundamental importance of non-collagenous matrix and suggesting that 30
regenerative medicine strategies should change focus from the fibrous to the non-collagenous 31
matrix phase of tissue. 32
33
Introduction 34
Functional adaptation of load-bearing tissues such as tendon is crucial to ensure the tissue is 35
specialised appropriately to meet functional needs. Adaptation to mechanical requirements is 36
key in healthy development and homeostatic tissue maintenance, with poor tissue 37
optimisation during maturation likely a key contributor to increased injury risk later in life. 38
Dysregulated homeostasis and long-term under- or over-stimulation leads to maladaptation, 39
changes in tissue integrity, and reduced mechanical competence and is implicated in the 40
disease aetiology of load-bearing tissues(Freedman et al., 2015; Gardner et al., 2008). 41
Understanding the developmental drivers of structural specialisation and their association 42
with mechanobiology is thus of fundamental importance for healthy ageing and disease 43
prevention in musculoskeletal tissues(R. Choi et al., 2018; Chavaunne T. Thorpe et al., 2013). 44
Such knowledge will help identify future targets for therapeutic interventions, and thus 45
address the current lack of effective musculoskeletal disease treatments with new, evidence-46
based approaches to disease management. However, there is currently little knowledge of the 47
key extracellular matrix (ECM) components associated with structural specialisation, the 48
temporal nature of their adaptation, or the stimuli that drive adaptation. 49
As the principal structural component of connective tissues, collagen expression at the gene 50
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
3
and protein level has been the focus of the majority of studies in relation to loading, with 51
some studies reporting increases in collagen synthesis and others noting collagen degradation 52
in response to loading, depending on the tissue function or tissue structure in different 53
species(R. Choi et al., 2018; Magnusson & Kjaer, 2019). In materials science, this collagen 54
structural framework is commonly referred to as the “fibre phase” of a material, surrounded 55
by the primarily non-collagenous and glycoprotein-rich components of the ECM, termed the 56
“matrix phase”(Armiento et al., 2018; C. T. Thorpe & Screen, 2016). This distinction is 57
important, as it describes a fibre composite material, in which “fibre” and “matrix” phases 58
have different mechanical properties, and overall tissue mechanical properties and function 59
are governed by the interplay of these two phases. When looking to understand functional 60
adaption of a tissue, it is necessary to look at adaption of all ECM components. 61
Whilst fibre phase adaption has received some attention, adaptation of the matrix phase to 62
mechanical stimuli remains poorly defined. Indeed, it is notable that the numerous studies 63
investigating the mechanoresponsive nature of load-bearing tissues tend to restrict their focus 64
to specific fibre or matrix components with no spatial distinction, and also focus on a single 65
element of either structural or mechanical adaptation, such that limited information is 66
gained(Cherdchutham, Becker, et al., 2001; R. K. Choi et al., 2019; Mendias et al., 2012). In 67
order to provide the necessary complete profile of adaptive behaviour, it is crucial that phase-68
specific, temporospatial adaptation in the context of both structure and function is defined. 69
Identifying the drivers of adaptation requires use of a model system in which the 70
temporospatial nature of adaptation can be fully profiled. Tendon provides the ideal model 71
for such a study. It is well-established that mature tendons can present structural and 72
mechanical specialisms(Chavaunne T. Thorpe et al., 2015; Chavaunne T. Thorpe, 73
Karunaseelan, et al., 2016; Chavaunne T. Thorpe, Riley, et al., 2016) and be grouped into two 74
clear functional groups; stiff positional tendons simply connect muscle to bone to effectively 75
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
4
position limbs, whilst elastic energy-storing tendons increase locomotor efficiency by 76
stretching and storing energy which they return to the system on recoil(Batson et al., 2010; C. 77
T. Thorpe & Screen, 2016; C T Thorpe et al., 2012). Further, the simple aligned organisation 78
of tendon means that fibre and matrix phases are spatially distinct, enabling structural and 79
mechanical characterisation of each phase independently, by comparing fascicles (fibre 80
phase) and inter-fascicular matrix (IFM; matrix phase)(C. T. Thorpe & Screen, 2016; C T 81
Thorpe et al., 2012). Finally, use of equine tendon provides access to an exceptional model of 82
adaptation. The equine superficial digital flexor tendon (SDFT) has been shown to be highly 83
analogous to the human Achilles tendon in its capacity for energy storage, injury profile and 84
extent of specialization(Biewener, 1998; Patterson-Kane & Rich, 2014). Availability of 85
samples enabled us to explore the extensive adaptation processes associated with late stage 86
development, contrasting paired positional and energy-storing equine tendons through pre- 87
and post-natal development. 88
Using this model, we investigate the process and drivers of functional adaptation, when 89
tendons transition from an absence of loading (foetal: mid to end (6 to 9 months) gestation, 90
and 0 days: full-term foetuses, and foals that did not weight-bear); through to weight-bearing 91
(0-1 month) and then to an increase in body weight and physical activity (3-6 months; and 1-92
2 years). We hypothesise that early in development during gestation, the fibre and matrix 93
phases of functionally distinct tendons have identical compositional profiles and mechanical 94
properties, with tissue specialisation occurring as an adaptive response to the mechanical 95
stimulus of load-bearing, predominantly in the matrix phase of the elastic energy-storing 96
tendon. 97
98
Results 99
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
5
Mechanical adaptation is localised to the matrix phase 100
First, we determined how the mechanical properties of the fibre and matrix phase develop in 101
tendon, with a particular focus on the temporospatial nature of mechanical adaptation to 102
functional specialisation. Individual fascicles were dissected and tested as fibre samples, 103
while an isolated region of interfascicular matrix, matrix phase, was tested by shearing 104
fascicles apart. Samples were subjected to preconditioning followed by a pull to failure 105
(Supplementary Figure 1). The yield point of samples was identified, denoting the point at 106
which the sample became irreversibly damaged and was unable to recover from the applied 107
load, and the sample failure properties also recorded, highlighting the maximum stress and 108
strain the sample could withstand. 109
A significant increase in fibre phase yield and failure properties was evident when comparing 110
embryonic fibre samples to those acquired immediately at birth. However, data indicate 111
minimal distinction in fibre phase mechanics between functionally distinct tendons (Figure 1) 112
and, significantly, no specialisation for energy storage in response to loading during postnatal 113
development. 114
Contrasting with fibre phase mechanics, the failure properties of the matrix phase continued 115
to alter throughout development with failure properties increasing markedly from 6 months 116
onwards. We also identify the emergence of an extended region of low stiffness at the start of 117
the loading curve (ie an extended toe region) specific to the SDFT matrix phase pull to failure 118
curve. This indicates less resistance to extension, and together with the concomitant increase 119
in matrix yield force and extension at yield, demonstrates development of an overall greater 120
capacity for extension in the SDFT matrix phase behaviour. A summary of these findings is 121
achieved by plotting the amount of matrix phase extension at different percentages of failure 122
force (Figure 2b,h-k), highlighting how the matrix phase of the energy-storing SDFT became 123
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
6
significantly less stiff than that of the positional CDET during the initial toe region of the 124
loading curve as the tendon adapts. 125
The viscoelastic properties of the developing matrix phase also showed significant 126
interactions between tendon type and development, with matrix viscoelasticity significantly 127
decreasing with development specifically in the energy-storing SDFT (Figure 2a,c-d), 128
resulting in specialisation towards a more energy efficient structure. 129
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
7
130
131
Figure 1. Fibre phase response to mechanical testing shows increase in strength with 132 development but few significant differences between tendon types, indicating that the fibre 133 phase shows minimal structural specialisation in response to loading. (a) Representative curves 134 for 10 preconditioning cycles for the SDFT and CDET fibre phase in the foetus and 1-2 years age 135 group. (b) Representative force-extension curves to failure for the SDFT and CDET fibre phase in the 136 same age groups. (c-i) Mean SDFT and CDET fibre phase biomechanical properties are presented 137 across development, with data grouped into age groups: foetus, 0 days (did not weight-bear), 0-1 138 month, 3-6 months, 1-2 years. ‡ significant interaction between tendon type and development, * 139 significant difference between tendons, a-b significant difference between age groups. Error bars 140 depict standard deviation. 141
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
8
142
Figure 2. Mechanical testing of the matrix phase shows an equivalent increase in failure 143 properties between the SDFT and CDET with development, but development of an extended 144 low stiffness toe region and more elastic behaviour in the SDFT. (a) Representative curves for 10 145 preconditioning cycles for the SDFT and CDET matrix phase in the foetus and 1-2 years age group. 146 (b) Representative force-extension curves to failure for the SDFT and CDET matrix phase in the same 147 age groups. (c-i) Mean SDFT and CDET matrix phase biomechanical properties are presented across 148 development, with data grouped into age groups: foetus, 0 days (did not weight-bear), 0-1 month, 3-6 149 months, 1-2 years. (j-k) To visualise the extended low stiffness toe region in the SDFT matrix phase, 150 the amount of matrix phase extension at increasing percentages of failure force is presented, 151 comparing the SDFT and CDET in the foetus and 1-2 years age group. ‡ significant interaction 152 between tendon type and development, * significant difference between tendons, a-g significant 153 difference between age groups. Error bars depict standard deviation. 154
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
9
155
Structural adaptation is localised to the matrix phase 156
Having described mechanical adaptation of the matrix phase to meet functional demand, we 157
next performed a histological and immunohistochemical comparison of developing energy-158
storing and positional tendons to determine how temporospatial structural adaptation may 159
dictate this evolving mechanical behaviour. 160
The energy-storing SDFT and positional CDET appeared histologically similar in the foetus, 161
in both instances showing surprisingly poor demarcation of the matrix phase, which only 162
became structurally distinct after birth and the initiation of loading (Figure 3a). Fibre 163
development was generally consistent in both tendon types with cellularity and crimp 164
showing a reduction with development, cells displaying more elongated nuclei, and collagen 165
showing a more linear organisation. In contrast, the matrix phase demonstrated divergence 166
between tendon types with only the SDFT matrix phase showing an increase in cellularity 167
following tendon loading and a retention of matrix phase width throughout development 168
(Figure 3, Supplementary Figure 2). 169
The abundance of major ECM proteins was also generally consistent across fibre and matrix 170
regions in the foetus, with divergence of protein composition between phases only evident 171
with further development. Notably adaptation was driven by changes in non-collagenous 172
ECM components specifically, levels of which reduced in the fibre phase and increased 173
dramatically in the matrix phase through postnatal development (Figure 3c, Supplementary 174
Figure 3). Of particular note, we demonstrate the distribution of PRG4 (commonly known as 175
lubricin) and TNC predominantly in the matrix phase of tendons. We also demonstrate that 176
elastin is preferentially localised to the matrix phase with its abundance decreasing only in 177
the CDET with development. Furthermore, we show how structural changes do not manifest 178
until after birth and the initiation of loading, but that structural adaptation to loading then 179
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
10
occurs over a period of months, involving both upregulation and downregulation of different 180
ECM constituents. 181
182
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
11
183
184
Figure 3. The SDFT and CDET are histologically similar at birth and differentiate with 185 development especially in the matrix phase. (a) Representative images of H&E sections of the 186 SDFT and CDET demonstrate structural development: foetus, 0 days (did not weight-bear), 0-1 year, 187 and 1-2 years whilst (b) Radar plots enable the mean histology scores of the fibre and matrix phase 188 for the SDFT and CDET to be compared between the foetus and 1-2 years age group (all data shown 189
in Supplementary Figure 2). A decrease in cell numbers, crimp, and matrix phase width is visible 190 with progression of age, and the aspect ratio of cells in the fibre phase increases. (c) Use of 191 immunohistochemical assays shows divergence of PGR4 (lubricin) and elastin with maturation 192 between functionally distinct tendons. Matrix and fibre phase staining scores are shown for decorin 193 (DCN), fibromodulin (FMOD), lubricin (PRG4), and tenascin-C (TNC) in the SDFT and CDET, 194 alongside representative images of immunohistochemical staining in the postnatal SDFT. A 195 quantitative measure of elastin (ELN) is provided as percentage of wet weight, alongside a 196 representative image of immunohistochemical staining in the postnatal SDFT. Staining scores for 197
elastin are provided in Supplementary Figure 3. ‡ significant change in tendon phase with 198 development, ‡‡ significant interaction between tendon phase and development, * significant 199 difference between tendons, a-d significant difference between age groups. Scale bar 100 µm. Error 200 bars depict standard deviation. 201
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
12
202
Adaptation relies on evolution of matrix phase composition only 203
To explore these concepts in further detail and to scrutinise the capacity for ECM adaptation, 204
proteomic methodologies were adopted. With the mechanical and histological data 205
identifying that functional adaptation is particular to the energy-storing SDFT, mass 206
spectrometry analysis focused on a more detailed comparison of the matrix and fibre phase 207
development and adaptation in this tendon specifically. 208
Our results demonstrated that the proteomic profile of the matrix phase was more complex 209
(more identified proteins) and a higher percentage of matrix phase proteins were cellular, 210
supporting the histological findings of a more cellular matrix phase (Supplementary Figure 211
4). Notably, despite the two phases being structurally distinct, they had 14 collagens and 11 212
proteoglycans in common (Supplementary Table 4). Overall, proteomic heatmap analysis 213
correlated very strongly with immunohistochemical findings, showing that alterations in the 214
fibre phase proteome reduced through development, with minimal changes following the 215
initiation of loading (Table 1 and 2, Figure 4a), whilst numerous matrisome and matrisome-216
related proteins progressively increase in abundance through development in the matrix phase 217
(Table 1 and 2). Detailed consideration of protein changes also highlights that post loading 218
changes in the matrix phase appear more specific to proteoglycans and glycoproteins. 219
Proteomic data also enable insight into the turnover of proteins in the different tendon phases, 220
through a comparison of the neopeptides produced by protein breakdown(Chavaunne T. 221
Thorpe, Peffers, et al., 2016). In the current study, we are able to profile the temporal nature 222
of fibre and matrix turnover, demonstrating that both phases display turnover during 223
development but that fibre phase turnover slows down towards the end of maturation, whilst 224
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
13
matrix phase turnover rates are maintained, suggesting structural and/or compositional 225
plasticity (Figure 4b). 226
Having identified the matrix phase as the location of functional adaptation, we next 227
investigated the regulation of this process, to detect targets for modulation in regeneration 228
strategies addressing functional impairment. Pathway analysis of the differentially abundant 229
proteins across age groups supported an ECM-integrin-cytoskeleton to nucleus signalling 230
pathway for the mediation of the observed mitogenesis and matrigenesis in response to 231
tendon loading. In addition, TGF-β1 was highlighted as a regulator of ECM organisation and 232
functional adaptation, upregulated in the energy-storing tendon following loading (Figure 4). 233
234
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
14
235 236 Figure 4. The fibre phase proteome remains the same during postnatal development and tendon 237 loading whereas the matrix phase starts changing following tendon loading in postnatal 238 development. (a) Heatmap of differentially abundant proteins in foetus, 0 days (did not weight-bear), 239 0-1 month, 3-6 months, and 1-2 years SDFT matrix and fibre phases (p<0.05, fold change ≥2). 240 Heatmap colour scale ranges from blue to white to red with blue representing lower abundance and 241 red higher abundance. (b) Proteins with identified neopeptides and proteins showing differential total 242 neopeptide abundance across age groups. Graph of proteins showing differential total neopeptide 243 abundance in the SDFT fibre phase across development (p<0.05, fold change≥2, FDR 5%). No 244 proteins showed differential total neopeptide abundance in the matrix phase. (c) IPA networks for 245 TGFB1 in the foetus and at 3-6 months in the SDFT matrix phase. TGFB1 regulation in the matrix 246 phase is predicted to be inhibited in the foetus and activated at 3-6 months in the SDFT. Red nodes, 247 upregulated proteins, green nodes, downregulated proteins, intensity of colour is related to higher 248 fold-change, orange nodes, predicted upregulated proteins in the dataset, blue nodes, predicted 249 downregulated proteins. (d) Whole tendon relative mRNA expression for TGFB1 in the SDFT and 250 CDET during postnatal development. * significant difference between tendons, a significant 251 difference between age groups. Error bars depict standard deviation. 252
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
15
253 Table 1. Matrix phase differentially abundant matrisome and matrisome-associated proteins 254 through development organised by highest mean condition (p<0.05, fold change≥2). Proteins are 255 arranged into colour coded divisions and categories. Bar graphs profile the relative abundance of each 256 protein at each development stage, with the development age reporting the highest mean protein level 257 also specified. 258
Protein Division Category Highest mean cond.
SERPINH1 Matrisome-associated ECM Regulators Foetus
COL14A1 Core matrisome Collagens 0-1 month
ASPN Core matrisome Proteoglycans 0-1 month
FMOD Core matrisome Proteoglycans 0-1 month
KERA Core matrisome Proteoglycans 0-1 month
FBLN5 Core matrisome ECM Glycoproteins 0-1 month
FGB Core matrisome ECM Glycoproteins 0-1 month
FGG Core matrisome ECM Glycoproteins 0-1 month
COL1A2 Core matrisome Collagens 3-6 months
COL2A1 Core matrisome Collagens 3-6 months
COL4A1 Core matrisome Collagens 3-6 months
COL4A2 Core matrisome Collagens 3-6 months
COL6A3 Core matrisome Collagens 3-6 months
BGN Core matrisome Proteoglycans 3-6 months
HSPG2 Core matrisome Proteoglycans 3-6 months
ADIPOQ Core matrisome ECM Glycoproteins 3-6 months
FBN1 Core matrisome ECM Glycoproteins 3-6 months
FN1 Core matrisome ECM Glycoproteins 3-6 months
LAMB2 Core matrisome ECM Glycoproteins 3-6 months
LAMC1 Core matrisome ECM Glycoproteins 3-6 months
NID1 Core matrisome ECM Glycoproteins 3-6 months
ANXA4 Matrisome-associated ECM-affiliated 3-6 months
S100A4 Matrisome-associated Secreted Factors 3-6 months
COL21A1 Core matrisome Collagens 1-2 years
COL3A1 Core matrisome Collagens 1-2 years
COL5A1 Core matrisome Collagens 1-2 years
COL5A2 Core matrisome Collagens 1-2 years
COL6A1 Core matrisome Collagens 1-2 years
COL6A2 Core matrisome Collagens 1-2 years
DCN Core matrisome Proteoglycans 1-2 years
LUM Core matrisome Proteoglycans 1-2 years
OGN Core matrisome Proteoglycans 1-2 years
PRELP Core matrisome Proteoglycans 1-2 years
COMP Core matrisome ECM Glycoproteins 1-2 years
DPT Core matrisome ECM Glycoproteins 1-2 years
TGFBI Core matrisome ECM Glycoproteins 1-2 years
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
16
259
Table 2. Fibre phase differentially abundant matrisome and matrisome-associated proteins 260 through development organised by highest mean condition (p<0.05, fold change≥2). Proteins are 261 arranged into colour coded divisions and categories. Bar graphs on the right profile the relative 262 abundance of each protein at each development stage, with the development age reporting the highest 263 mean protein level also specified. 264
265
266
Discussion 267
In this study, we describe the process and drivers of functional adaptation in tendon 268
development integrating mechanical, structural, and compositional analysis in tendons 269
transitioning from an absence of loading through to weight-bearing and then to an increase in 270
body weight and physical activity. Whilst the limited previously available data on the 271
development of tendon gross mechanical properties show an increase in mechanical 272
properties with development(Ansorge et al., 2011; Cherdchutham, Meershoek, et al., 2001), 273
no such phase-specific analysis of the development of tissue mechanics has been carried out 274
previously. Similarly, available research into tendon morphogenesis and maturation has 275
Protein Division Category Highest mean cond.
COL11A1 Core matrisome Collagens Foetus
DCN Core matrisome Proteoglycans Foetus
FMOD Core matrisome Proteoglycans Foetus
KERA Core matrisome Proteoglycans Foetus
PCOLCE Core matrisome ECM Glycoproteins Foetus
SERPINF1 Matrisome-associated ECM Regulators Foetus
ANXA1 Matrisome-associated ECM-affiliated Proteins Foetus
ANXA2 Matrisome-associated ECM-affiliated Proteins Foetus
ANXA5 Matrisome-associated ECM-affiliated Proteins Foetus
LGALS1 Matrisome-associated ECM-affiliated Proteins Foetus
COL12A1 Core matrisome Collagens 0 days
COL3A1 Core matrisome Collagens 1-2 years
PRELP Core matrisome Proteoglycans 1-2 years
COMP Core matrisome ECM Glycoproteins 1-2 years
FN1 Core matrisome ECM Glycoproteins 1-2 years
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
17
previously focused on the development of the collagenous network that comprises the fibrous 276
phase of the tendon and is often focussed on early foetal development(Kalson et al., 2011; 277
Marturano et al., 2013; Pan et al., 2018). 278
Here, examining the fibre and matrix phase mechanical properties independently, we show 279
minimal distinction in fibre phase mechanics between functionally distinct tendons and, 280
significantly, no specialisation for energy storage in response to loading during postnatal 281
development. In contrast, the matrix phase mechanical properties display continuous 282
alterations through development with properties in the foetus being comparable between 283
functionally distinct tendons, and a low stiffness region emerging in the initial non-linear 284
region (toe region) of the pull to failure curve of the SDFT matrix phase only following 285
tendon loading postnatally. This is coupled with a concomitant increase in matrix force and 286
extension at yield, point at which the sample became irreversibly damaged, highlighting that 287
the energy-storing SDFT matrix phase becomes significantly less stiff than that of the 288
positional CDET during the initial toe region of the loading curve. We have previously 289
indicated that this low stiffness behaviour allows sliding between the fascicles of the fibre 290
phase, enabling non-uniform loading of tissue and is fundamental for effective extension and 291
recoil in energy-storing tendons(Chavaunne T. Thorpe et al., 2015). Furthermore, with ageing 292
the low stiffness behaviour of the matrix phase of energy-storing tendons is lost, possibly 293
contributing to disease development(Chavaunne T. Thorpe et al., 2013). The only other 294
studies considering the mechanical properties of developing tendons have focused simply on 295
changes in whole tissue mechanics, and have thus not been able to identify the drivers of 296
change within the tissue(Ansorge et al., 2011; Cherdchutham, Meershoek, et al., 2001). Here, 297
we identify that the matrix phase is the key region in which mechanical adaptation to meet 298
function occurs, and that this occurs after the initiation of loading, primarily 1-2 years 299
postnatally. 300
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
18
We subsequently examine how temporospatial structural adaptation may dictate this evolving 301
mechanical behaviour and uncover a divergence in structural characteristics between tendon 302
types in the matrix phase only, with a retention of matrix phase width throughout 303
development and an increase in cellularity in the SDFT matrix phase only. It is well 304
recognised that foetal and early postnatal tendons are highly cellular, and cellularity is 305
generally considered to decrease postnatally(Russo et al., 2015; Stanley et al., 2008), but here 306
we show that the described reduction in cellularity only occurs in the fibre phase, and 307
cellularity in fact increases in the matrix phase with development. By following the 308
alterations in cellularity across fibre and matrix, here we can determine that the marked 309
difference in regional cellularity is likely driven by a maintenance of cell numbers following 310
tendon loading in the thinning matrix region, while cell numbers in the fibre region appear to 311
reduce as a result of the fibre phase ECM increase. Greater cellularity is commonly 312
associated with a requirement for rapid adaptive organisation of ECM components(Russo et 313
al., 2015), suggesting the matrix phase, particularly in the energy-storing tendons, may adapt 314
to be more mechanoresponsive, a necessary aspect of healthy homeostatic maintenance of a 315
tissue. Immunohistochemical analysis reveals the distribution of major ECM proteins is 316
consistent across tendons in the foetus and becomes distinct across phases through 317
development. Of note, PRG4 (lubricin), a large proteoglycan which is important in ECM 318
lubrication, is found mainly distributed in the matrix phase of tendons. Using a lubricin-319
knockout mouse, this proteoglycan has been demonstrated to facilitate interfascicular 320
sliding(Kohrs et al., 2011), indicating that this structural adaptation may be key in achieving 321
the previously identified mechanical adaptation in the energy-storing tendon matrix phase. In 322
addition, Kostrominova and Brooks (2013)(Kostrominova & Brooks, 2013) report PRG4 323
expression as wells as elastin expression decreased with ageing in rat tendon suggesting an 324
association with an increased risk of disease with ageing. We also demonstrate that elastin is 325
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
19
preferentially localised to the matrix phase, potentially having a role in the capacity for 326
matrix recoil after loading which is necessary for the healthy function of energy-storing 327
tendons(Godinho et al., 2017; Ritty et al., 2002). Further supporting a role for elastin in the 328
energy-storing function, elastin appears to be redundant in positional tendons with its 329
abundance decreasing in the CDET with development. Together, these findings show that 330
structural adaptation of tendon post loading is primarily focused to the matrix phase, and 331
observed predominantly in the energy-storing SDFT. 332
Compositional analysis of the energy-storing SDFT phases using mass spectrometry 333
corroborates the immunohistochemical analysis and shows a more complex proteomic profile 334
for the matrix phase. It additionally shows that abundance of the majority of proteins in the 335
fibre phase is higher in the foetus and reduces through development with minimal changes 336
following the initiation of loading, whereas in the matrix phase numerous ECM and ECM-337
related proteins progressively increase in abundance following tendon loading and through 338
development. Neopeptide analysis demonstrated fibre phase ECM protein turnover slows 339
down towards the end of maturation, whilst matrix phase ECM protein turnover rates are 340
maintained. Once a tendon is mature, little collagen turnover occurs(Birch, 2007; KM et al., 341
2013) and we have previously shown that the minimal turnover in mature tendon is focused 342
to the matrix phase(C. T. Thorpe et al., 2015; Chavaunne T. Thorpe et al., 2010; Chavaunne 343
T. Thorpe, Peffers, et al., 2016). The maintenance of turnover rates observed in the matrix 344
phase here suggests structural and/or compositional plasticity of the matrix phase. Integrated, 345
our data convincingly show a continual temporal change in the matrix phase proteome 346
specifically, which would enable adaptation and specialisation to the load environment, and 347
highlight the compositional plasticity of the matrix phase in responding to dynamic altered 348
conditions such as those occurring during development and regeneration. It is critical that the 349
difference in capacity for functional adaptation across fibre and matrix phases identified here 350
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
20
is considered if regenerative medicine and tissue engineering approaches are to be successful. 351
Here, we demonstrate the temporal pattern of structure-function adaptation, with 352
compositional changes occurring in the first months after loading, and leading to the 353
mechanical specialisation we have previously observed in adult energy-storing tendon(Birch, 354
2007; C T Thorpe et al., 2012; Chavaunne T. Thorpe et al., 2015). With the fibrous phase 355
primarily responsible for the mechanical strength of a tissue, biomaterial and regenerative 356
medicine studies have unsurprisingly placed considerable emphasis on this region to 357
date(Sensini et al., 2019; Watts et al., 2017). Here, we not only highlight the importance of 358
the matrix phase in modulating mechanical behaviour, but also demonstrate how the matrix 359
phase must be targeted to support adaptation and optimum tissue quality. 360
Finally, pathway analysis of our proteomic data highlighted TGF-β1 as a regulator of ECM 361
organisation and functional adaptation, predicted to be upregulated following loading in the 362
energy-storing tendon. TGF-β is known to have a role in cellular mechanobiology and 363
connective tissue homeostasis, regulating ECM synthesis and remodelling in a force-364
dependent way following mechanical stimulation, to specify the quality of the ECM and help 365
coordinate cytoskeletal tension(Maeda et al., 2011). A previous study of developing chick 366
tendon detected TGF-β1 staining in the matrix phase only during development, highlighting 367
its localised distribution in development(Kuo et al., 2008). In the current study, we are also 368
able to associate TGF- expression with functional adaptation of the matrix phase of tendon. 369
In addition to tissue development and homeostasis, TGF-β1 is involved in connective tissue 370
injury and repair with abnormal expression levels reported in both processes suggesting a 371
pleiotropic mode of action(Gao et al., 2019). The above may suggest a role for TGF-β1 in 372
tissue development and homeostasis and that its dysregulation is associated with tissue injury 373
and repair expression levels. 374
375
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
21
Outlook 376
We demonstrate for the first time that functional adaptation in tendon is predominantly reliant 377
on adaptation of the metabolically active matrix phase, which responds to the mechanical 378
environment through TGF- signalling, resulting in modulations in ECM turnover and 379
composition to fine-tune mechanical properties. Traditionally, the matrix phase of connective 380
tissues has received considerably less attention than the fibre phase, with regenerative 381
medicine, biomimetics and biomechanics studies all largely focused on investigating and 382
recapitulating the organisation and mechanical properties of the collagenous fibrous network. 383
Following tendon injury, normal tissue architecture is not recovered, and in particular, the 384
cellular matrix phase is not regenerated. There is great potential gain from understanding the 385
convergence of biology underpinning adaptation, function and pathology and here, we 386
propose a paradigm shift to consider the metabolically active matrix phase as a key target for 387
regenerative medicine strategies aimed at addressing functional impairment of tendons and 388
other connective tissues following disease. Regeneration of the matrix phase following 389
tendon injury could be key for tendon health and low re-injury risk. 390
391
Materials and Methods 392
Experimental design 393
Using an equine tendon model, we investigate the process and drivers of functional 394
adaptation in the SDFT and CDET, two functionally distinct tendons, when tendons transition 395
from an absence of loading (foetal: mid to end (6 to 9 months) gestation, and 0 days: full-396
term foetuses, and foals that did not weight-bear); through to weight-bearing (0-1 month) and 397
then to an increase in body weight and physical activity (3-6 months; and 1-2 years). We use 398
a phase-specific approach to characterise each tendon phase independently, by comparing 399
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
22
fascicles (fibre phase) and inter-fascicular matrix (IFM; matrix phase) mechanical properties, 400
structure and composition. 401
For this purpose, we used mechanical testing, histological and immunohistochemical analysis 402
and mass spectrometry analysis following laser capture microdissection. Sample size was 403
selected based on previous experiments and restricted by sample availability and the cost of 404
mass spectrometry analysis. 405
Sample collection 406
Both forelimbs were collected from foetuses and foals aged 0-2 years (n=19) euthanised for 407
reasons unrelated to this project at a commercial abattoir or equine practices following owner 408
consent under ethical approval for use of the cadaveric material granted by the Veterinary 409
Research Ethics Committee, School of Veterinary Science, University of Liverpool 410
(VREC352). Collected tendons were split in the following age groups: Foetus (between 6 and 411
9 months of gestation; n=4); 0 days (full-term foetuses (average gestation 11-12 months) and 412
foals that did not weight-bear; n=4): 0-1 month (n=3); 3-6 months (n=4); 1-2 years (n=4). 413
The SDFT and CDET from one forelimb were dissected and wrapped in phosphate-buffered 414
saline dampened tissue paper and foil and stored at -80 oC for biomechanical testing. Two 1-2 415
cm segments from the mid-metacarpal area of the SDFT and CDET of the other forelimb 416
were dissected, and one fixed in 4% paraformaldehyde for histology and 417
immunohistochemistry, and the other snap frozen in isopentane and stored at -80 oC for laser 418
capture microdissection. 419
Biomechanical testing of the fibre phase 420
On the day of testing, samples were defrosted within their tissue paper wrap, then 421
immediately prepared for testing. Fascicles (fibre phase samples) were dissected from the 422
mid-metacarpal region of the SDFT and CDET and subjected to a quasi-static test to failure 423
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
23
according to Thorpe et al. (2015)(Chavaunne T. Thorpe et al., 2015). Briefly, prior to testing, 424
the diameter of each fascicle was measured along a 1 cm length in the middle of the fascicle 425
with a non-contact laser micrometre (LSM-501, Mitotuyo, Japan, resolution = 0.5 um) and 426
the smallest diameter recorded and used to calculate cross-sectional area (CSA), assuming a 427
circular shape. 428
Fibre phase samples were loaded in an electrodynamic testing machine (Instron ElectroPuls 429
1000) equipped with a 250 N load cell and pneumatic grips (4 bar) coated with rubber and 430
sandpaper to prevent sample slippage(C T Thorpe et al., 2012). The distance between the 431
grips was set to 20 mm and fibre phases preloaded to 0.1 N (approx. 2% fibre phase failure 432
load) to remove any slack in the sample. Following preload, the distance between the grips 433
was recorded as the gauge length, then fibre phase samples preconditioned with 10 loading 434
cycles between 0 and 3% strain (approximately 25% failure strain) using a sine wave at 1 Hz 435
frequency. Immediately after preconditioning, fibre samples were pulled to failure at a strain 436
rate of 5%/s. Force and extension data were continuously recorded at 100 Hz during both 437
preconditioning and the quasi-static test to failure. Acquired data were smoothed to reduce 438
noise before calculations with a 3rd order Savitzky-Golay low pass filter, with a frame of 15 439
for the preconditioning data and 51 for the pull to failure data. 440
Using the preconditioning data, the total percentage hysteresis and stress relaxation were 441
calculated, between the first and last preconditioning cycle. Failure force, extension, stress, 442
and strain were calculated from the test to failure, and a continuous modulus calculated 443
across every 10 data points of each stress strain curve, from which the maximum modulus 444
value was determined. The point of maximum modulus was defined as the yield point from 445
which yield stress and yield strain were determined. 446
Biomechanical testing of the matrix phase 447
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
24
On the day of testing, tendons were defrosted within their tissue paper wrap, and matrix 448
phase samples immediately dissected and prepared for biomechanical testing as described 449
previously by Thorpe et al. (2012)(C T Thorpe et al., 2012). Briefly, a group of two adjacent 450
intact fascicles (bound by the matrix phase) were dissected, after which the opposing end of 451
each fascicle was cut transversely 10 mm apart, to leave a consistent 10 mm length of intact 452
matrix phase that could be tested in shear (Supplementary Figure 1). 453
Utilising the same electrodynamic testing machine and pneumatic grips as described for the 454
fibre phase, the intact end of each fascicle was gripped with a grip to grip distance of 20 mm, 455
and a pre-load of 0.02 N (approx. 1% matrix phase failure load) applied. Matrix phase 456
samples were preconditioned with 10 cycles between 0 and 0.5 mm extension (approx. 25% 457
failure extension) using a sine wave at 1 Hz frequency, then pulled to failure at a speed of 1 458
mm/s. Force and extension data were continuously recorded at 100 Hz during both 459
preconditioning and the quasi-static test to failure. Acquired data was smoothed to reduce 460
noise before calculations with a 3rd order Savitzky-Golay low pass filter, with a frame of 15 461
for the preconditioning data and 51 for the pull to failure data. 462
Total percentage hysteresis and stress relaxation were again calculated between the first and 463
last preconditioning cycle. Failure force and extension were determined from the quasi-static 464
pull to failure curve, and a continual stiffness curve was calculated across every 10 data 465
points of the curve, from which maximum stiffness was determined, and yield force and yield 466
extension at maximum stiffness reported. Based on previous data demonstrating notable 467
differences in the toe region of the matrix phase curve of functionally distinct tendons, the 468
shape of failure curves was also compared between samples by calculating the amount of 469
matrix phase extension at different percentages of matrix phase failure load(Chavaunne T. 470
Thorpe et al., 2015). 471
Histology scoring 472
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
25
Paraformaldehyde-fixed paraffin-embedded longitudinal SDFT and CDET segments were 473
sectioned at 6 µm thickness and stained with H&E for histologic examination and scoring 474
(n=13; 3 from each age group, 4 from 1-2 years age group). The examined histologic 475
variables are reported in Supplementary Table 1. 476
For parameters scored by investigators, the sections were blinded and histologic variables 477
assigned a grade from 0 to 3 by two independent investigators. Weighted Kappa showed 478
moderate to good agreement in all instances, hence the average of the two scores was used. 479
Other histologic variables were measured using image analysis (TissueFaxs, Tissuegnostics 480
and Adobe Photoshop CS3) and then assigned a grade from 0 to 3. Cumulative scores for the 481
fibre and matrix phase for each horse were obtained by summing the scores of the fibre and 482
matrix phase variables, respectively, excluding matrix phase percentage to ensure matrix 483
phase dimensions were not over-weighted in final reporting. 484
Immunohistochemistry 485
Immunohistochemical analysis for DCN, FMOD, PRG4, TNC and ELN was carried out on 486
paraformaldehyde-fixed paraffin-embedded longitudinal SDFT and CDET sections (6 µm 487
thickness) (n=12; 3 from each age group) as previously described by Zamboulis et al. 488
(2013)(Zamboulis et al., 2013). Antigen retrieval was carried out with 0.2 U/mL 489
Chondroitinase ABC (C2905, Sigma, Merck, Darmstadt, Germany) at 37 oC for two hours for 490
DCN, FMOD, PRG4, and TNC or with 4800 U/mL hyaluronidase (H3506, Sigma, Merck, 491
Darmstadt, Germany) at 37 oC for two hours for ELN. Primary antibodies were used at a 492
concentration of 1:1500 for DCN (mouse IgG), 1:400 for FMOD (rabbit IgG), 1:200 for 493
PRG4 (mouse IgG), 1:250 for TNC (mouse IgG, sc-59884, Santa Cruz Biotechnology, 494
Dallas, Texas), and 1:100 for ELN (mouse IgG, ab9519, Abcam, Cambridge, UK). 495
Antibodies for DCN and PRG4 were a kind gift from Prof. Caterson, Cardiff University, UK, 496
and the FMOD antibody was kindly provided by Prof. Roughley, McGill University, Canada. 497
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
26
The secondary antibody incubation was performed with the Zytochem Plus HRP Polymer 498
anti-rabbit for FMOD and anti-mouse for DCN, PRG4, TNC, and ELN (ZUC032-006 and 499
ZUC050-006, Zytomed Systems, Berlin, Germany). Immunohistochemical staining was 500
graded from 0 to 3 (low to high) on blinded sections, assessing stained area and staining 501
intensity for DCN, FMOD, TNC, and ELN. For PRG4, where staining was confined to the 502
pericellular area, staining intensity was measured using TissueFaxs (Tissuegnostics). 503
Quantification of tendon elastin 504
The elastin content of SDFT and CDET samples from each age group (n=12; 3 from each 505
age group) was quantified using the FASTINTM Elastin Assay (Biocolor, Carrickfergus, 506
UK)(Godinho et al., 2017). Briefly, SDFT and CDET tissue was powdered (~15 mg wet 507
weight) and incubated with 750 µl of 0.25 M oxalic acid at 100 °C for 2 one hour cycles to 508
extract all soluble a-elastin from the tissue. Preliminary tests showed two extractions were 509
sufficient to solubilise all a-elastin from developing SDFT and CDET. Following 510
extraction, samples and standards were processed in duplicate according to the 511
manufacturer’s instructions and their absorbance determined spectrophotometrically at 512
513 nm (Spectrostar Nano microplate reader, BMG Labtech, Aylesbury, UK). A standard 513
curve was used to calculate the samples’ elastin concentration and elastin was expressed as 514
a percentage of tendon wet weight. 515
Laser-capture microdissection 516
Laser-capture microdissection was used to collect samples from the fibre and matrix phase of 517
SDFT samples from all age groups (n=4 for each age group with the exception of the 0-1 518
month group where n=3). For this purpose, 12 µm transverse cryosections were cut from the 519
SDFT samples and mounted on steel frame membrane slides (1.4 µm PET membrane, Leica 520
Microsystems, Wetzlar, Germany). Frozen sections were dehydrated in 70% and 100% ice-521
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
27
cold ethanol, allowed to briefly dry, and regions of fibre and matrix phase laser-captured on 522
an LMD7000 laser microdissection microscope (Leica Microsystems, Wetzlar, Germany) and 523
collected in LC/MS grade water (FisherScientific, Hampton, New Hampshire). Collected 524
samples were immediately snap frozen and stored at -80oC for mass spectrometry analysis. 525
Mass spectrometry analysis 526
Mass spectrometry analysis of laser-captured SDFT matrix and fibre phase samples was 527
carried out as previously described by Thorpe et al. (2016)(Chavaunne T. Thorpe, Peffers, et 528
al., 2016). Samples were digested for mass spectrometry analysis with incubation in 0.1% 529
(w/v) Rapigest (Waters, Herts, UK) for 30 min at room temperature followed by 60 min at 60 530
°C and subsequent trypsin digestion. LC MS/MS was carried out at the University of 531
Liverpool Centre for Proteome Research using an Ultimate 3000 Nano system 532
(Dionex/Thermo Fisher Scientific, Waltham, Massachusetts) for peptide separation coupled 533
online to a Q-Exactive Quadrupole-Orbitrap mass spectrometer (Thermo Scientific, 534
Waltham, Massachusetts) for MS/MS acquisition. Initial ranging runs on short gradients were 535
carried out to determine the sample volume to be loaded on the column and subsequently 536
between 1-9 µL of sample was loaded onto the column on a one hour gradient with an inter-537
sample 30 min blank. 538
Protein identification and label-free quantification 539
Fibre and matrix phase proteins were identified using Peaks® 8.5 PTM software 540
(Bioinformatics Solutions, Waterloo, Canada), searching against the UniHorse database 541
(http://www.uniprot.org/proteomes/). Search parameters used were: peptide mass tolerance 542
10 ppm, fragment mass tolerance 0.01 Da, fixed modification carbamidomethylation, variable 543
modifications methionine oxidation and hydroxylation. Search results for peptide 544
identification were filtered with a false discovery rate (FDR) of 1%, and for protein 545
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
28
identification with a minimum of 2 unique peptides per protein, and a confidence score >20 (-546
10lgp>20). Label-free quantification was also carried out using Peaks® 8.5 PTM software for 547
the SDFT fibre and matrix phase separately. Protein abundances were normalised for 548
collected laser-capture area and volume loaded onto the mass spectrometry column and 549
differentially abundant proteins between the age groups in the SDFT fibre and matrix phase 550
were identified using a fold change ≥2 and p<0.05 (PEAKS adjusted p values). The mass 551
spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via 552
the PRIDE partner repository, with the dataset identifier PXD012169 and 553
10.6019/PXD012169. 554
Gene ontology and network analysis 555
The dataset of identified proteins in the SDFT fibre and matrix phase were classified for cell 556
compartment association with the Ingenuity Pathway Analysis software (IPA, Qiagen, 557
Hilden, Germany) and for matrisome categories with The Matrisome Project database(Hynes 558
& Naba, 2012). Protein pathway analysis for the differentially abundant proteins between age 559
groups in the SDFT fibre and matrix phase was carried out in IPA. Protein interactions maps 560
were created in IPA allowing for experimental evidence and highly predicted functional 561
links. 562
Neopeptide identification 563
For neopeptide identification, mass spectrometry data was analysed using Mascot server 564
(Matrix Science) with the search parameters: enzyme semiTrypsin, peptide mass tolerance 10 565
ppm, fragment mass tolerance 0.01 Da, charge 2+ and 3+ ions, and missed cleavages 1. The 566
included modifications were: fixed carbamidomethyl cysteine, variables oxidation of 567
methionine, proline, and lysine, and the instrument type selected was electrospray ionization-568
TRAP (ESI-TRAP). The Mascot-derived ion score was used to determine true matches 569
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
29
(p<0.05), where p was the probability that an observed match was a random event. The 570
peptide list was exported and processed with the Neopeptide Analyser, a software tool for the 571
discovery of neopeptides in proteomic data(Peffers et al., 2017). Obtained neopeptide 572
abundances for each sample were normalised for total peptide abundance for that protein and 573
sample, and normalised neopeptide abundances were subsequently summed for each protein 574
and the total neopeptide abundance analysed for differential abundance across the age groups 575
in the SDFT fibre and matrix phase using p<0.05 and FDR 5% (ANOVA and Benjamini-576
Hochberg FDR). 577
Relative mRNA expression 578
RNA extraction from whole SDFT and CDET was carried out followed by reverse 579
transcription. Quantitative real-time PCR (qRT-PCR) was performed on an ABI7300 system 580
(Thermo Fisher Scientific Waltham, Massachusetts) using the Takyon ROX SYBR 2X 581
MasterMix (Eurogentec, Liege, Belgium). qRT-PCR was undertaken using gene-specific 582
primers for DCN, FMOD, BGN, COMP, COL1A1, COL1A2, COL3A1, TGFB1, and 583
GAPDH as a reference gene previously validated (Supplementary Table 2). Relative 584
expression levels were normalised to GAPDH expression and calculated with the formula 585
E−ΔCt following primer efficiency calculation. 586
Statistical analysis 587
Statistical analysis was carried out in SigmaPlot (Systat Software Inc, San Jose, California) 588
unless otherwise stated. Details of the n numbers for each experiment and the statistical test 589
used for the analysis of the data are listed in Supplementary Table 3. Heatmaps were 590
designed in GProX(Rigbolt et al., 2011). The Central Limit Theorem (CLT) was used to 591
assume normality where n>30 and where n<30 normality was tested using the Shapiro-Wilks 592
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
30
test. If data were found not to be normally distributed their log10 transformation or ANOVA 593
on Ranks was used for statistical analysis but the original data was presented in graphs. 594
595
Acknowledgements 596
This work was funded by the Horserace Betting Levy Board, PRJ/776. We would like to 597
acknowledge the equine practices that provided samples for this study. 598
599
Author Contributions 600
DEZ designed and performed experiments, analysed the data, and wrote the manuscript. 601
CTT assisted with study design, data analysis, and edited the manuscript. YAK assisted 602
with data collection and analysis. HLB, HRCS, PDC conceived the study, assisted with 603
data analysis, and edited the manuscript. 604
605
Competing Interests statement 606
The authors declare that they have no competing interests. 607
608
Data and materials availability 609
The mass spectrometry proteomics data have been deposited to the ProteomeXchange 610
Consortium via the PRIDE partner repository, with the dataset identifier PXD012169 and 611
10.6019/PXD012169. 612
613
References 614
Ansorge, H. L., Adams, S., Birk, D. E., & Soslowsky, L. J. (2011). Mechanical, 615
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
31
compositional, and structural properties of the post-natal mouse Achilles tendon. Annals 616
of Biomedical Engineering, 39(7), 1904–1913. https://doi.org/10.1007/s10439-011-617
0299-0 618
Armiento, A. R., Stoddart, M. J., Alini, M., & Eglin, D. (2018). Biomaterials for articular 619
cartilage tissue engineering: Learning from biology. Acta Biomaterialia, 65, 1–20. 620
https://doi.org/10.1016/j.actbio.2017.11.021 621
Batson, E. L., Paramour, R. J., Smith, T. J., Birch, H. L., Patterson-Kane, J. C., & Goodship, 622
A. E. (2010). Are the material properties and matrix composition of equine flexor and 623
extensor tendons determined by their functions? Equine Veterinary Journal, 35(3), 314–624
318. https://doi.org/10.2746/042516403776148327 625
Biewener, A. A. (1998). Muscle-tendon stresses and elastic energy storage during locomotion 626
in the horse. Comparative Biochemistry and Physiology - B Biochemistry and Molecular 627
Biology, 120(1), 73–87. https://doi.org/10.1016/S0305-0491(98)00024-8 628
Birch, H. L. (2007). Tendon matrix composition and turnover in relation to functional 629
requirements. International Journal of Experimental Pathology, 88(4), 241–248. 630
https://doi.org/10.1111/j.1365-2613.2007.00552.x 631
Cherdchutham, W., Becker, C. K., Spek, E. R., Voorhout, W. E., & Van Weeren, P. R. 632
(2001). Effects of exercise on the diameter of collagen fibrils in the central core and 633
periphery of the superficial digital flexor tendon in foals. American Journal of 634
Veterinary Research, 62(10), 1563–1570. https://doi.org/10.2460/ajvr.2001.62.1563 635
Cherdchutham, W., Meershoek, L. S., Weeren, P. R. Van, & Barneveld, A. (2001). Effects of 636
exercise on biomechanical properties of the superficial digital flexor tendon in foals. 637
American Journal of Veterinary Research, 62(12), 1859–1864. https://avmajournals-638
avma-org.proxy1.cl.msu.edu/doi/pdf/10.2460/ajvr.2001.62.1859 639
Choi, R. K., Smith, M. M., Smith, S., Little, C. B., & Clarke, E. C. (2019). Functionally 640
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
32
distinct tendons have different biomechanical, biochemical and histological responses to 641
in vitro unloading. Journal of Biomechanics, 95, 109321. 642
https://doi.org/10.1016/j.jbiomech.2019.109321 643
Choi, R., Smith, M., Clarke, E., & Little, C. (2018). Cellular, matrix, and mechano-biological 644
differences in load-bearing versus positional tendons throughout development and 645
aging: a narrative review. Connective Tissue Research, 59(5), 483–494. 646
https://doi.org/10.1080/03008207.2018.1504929 647
Freedman, B. R., Bade, N. D., Riggin, C. N., Zhang, S., Haines, P. G., Ong, K. L., & Janmey, 648
P. A. (2015). The (dys)functional extracellular matrix. Biochimica et Biophysica Acta - 649
Molecular Cell Research, 1853(11), 3153–3164. 650
https://doi.org/10.1016/j.bbamcr.2015.04.015 651
Gao, F., Li, C., Zhou, J., Shen, X., Hu, B., Lu, M., Liu, Y., Zhang, B., Fang, Y., & Liu, Y. 652
(2019). Progress on relationship between transforming growth factor-beta1 and 653
tendinopathy. China Journal of Orthopaedics and Traumatology, 32(4), 377–382. 654
Gardner, K., Arnoczky, S. P., Caballero, O., & Lavagnino, M. (2008). The effect of stress-655
deprivation and cyclic loading on the TIMP/MMP ratio in tendon cells: An in vitro 656
experimental study. Disability and Rehabilitation, 30(20–22), 1523–1529. 657
https://doi.org/10.1080/09638280701785395 658
Godinho, M. S. C., Thorpe, C. T., Greenwald, S. E., & Screen, H. R. C. (2017). Elastin is 659
Localised to the Interfascicular Matrix of Energy Storing Tendons and Becomes 660
Increasingly Disorganised With Ageing. Scientific Reports, 7(1), 1–11. 661
https://doi.org/10.1038/s41598-017-09995-4 662
Hynes, R. O., & Naba, A. (2012). Overview of the matrisome-An inventory of extracellular 663
matrix constituents and functions. Cold Spring Harbor Perspectives in Biology, 4(1), 1–664
16. https://doi.org/10.1101/cshperspect.a004903 665
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
33
Kalson, N. S., Holmes, D. F., Herchenhan, A., Lu, Y., Starborg, T., & Kadler, K. E. (2011). 666
Slow stretching that mimics embryonic growth rate stimulates structural and mechanical 667
development of tendon-like tissue in vitro. Developmental Dynamics, 240(11), 2520–668
2528. https://doi.org/10.1002/dvdy.22760 669
KM, H., P, S., J, H., SP, M., & M, K. (2013). Lack of tissue renewal in human adult Achilles 670
tendon is revealed by nuclear bomb 14C (pp. 2074–2079). 671
Kohrs, R. T., Zhao, C., Sun, Y. L., Jay, G. D., Zhang, L., Warman, M. L., An, K. N., & 672
Amadio, P. C. (2011). Tendon fascicle gliding in wild type, heterozygous, and lubricin 673
knockout mice. Journal of Orthopaedic Research, 29(3), 384–389. 674
https://doi.org/10.1002/jor.21247 675
Kostrominova, T. Y., & Brooks, S. V. (2013). Age-related changes in structure and 676
extracellular matrix protein expression levels in rat tendons. Age, 35(6), 2203–2214. 677
https://doi.org/10.1007/s11357-013-9514-2 678
Kuo, C., Petersen, B., & Tuan, R. (2008). Spatiotemporal protein distribution of TGF-ß’s, 679
their receptors, and extracellular matrix molecules during embryonic tendon 680
development. Developmental Dynamics, 237(5), 1477–1489. 681
https://doi.org/10.1002/dvdy.21547.Spatiotemporal 682
Maeda, T., Sakabe, T., Sunaga, A., Sakai, K., Rivera, A. L., Keene, D. R., Sasaki, T., 683
Stavnezer, E., Iannotti, J., Schweitzer, R., Ilic, D., Baskaran, H., & Sakai, T. (2011). 684
Conversion of mechanical force into TGF-β-mediated biochemical signals. Current 685
Biology, 21(11), 933–941. https://doi.org/10.1016/j.cortex.2009.08.003.Predictive 686
Magnusson, S. P., & Kjaer, M. (2019). The impact of loading, unloading, ageing and injury 687
on the human tendon. Journal of Physiology, 597(5), 1283–1298. 688
https://doi.org/10.1113/JP275450 689
Marturano, J. E., Arena, J. D., Schiller, Z. A., Georgakoudi, I., & Kuo, C. K. (2013). 690
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
34
Characterization of mechanical and biochemical properties of developing embryonic 691
tendon. Proceedings of the National Academy of Sciences of the United States of 692
America, 110(16), 6370–6375. https://doi.org/10.1073/pnas.1300135110 693
Mendias, C. L., Gumucio, J. P., & Lynch, E. B. (2012). Mechanical loading and TGF-β 694
change the expression of multiple miRNAs in tendon fibroblasts. Journal of Applied 695
Physiology, 113(1), 56–62. https://doi.org/10.1152/japplphysiol.00301.2012 696
Pan, X. S., Li, J., Brown, E. B., & Kuo, C. K. (2018). Embryo movements regulate tendon 697
mechanical property development. Philosophical Transactions of the Royal Society B: 698
Biological Sciences, 373(1759). https://doi.org/10.1098/rstb.2017.0325 699
Patterson-Kane, J. C., & Rich, T. (2014). Achilles tendon injuries in elite athletes: Lessons in 700
pathophysiology from their equine Counterparts. ILAR Journal, 55(1), 86–99. 701
https://doi.org/10.1093/ilar/ilu004 702
Peffers, M. J., Jones, A. R., McCabe, A., & Anderson, J. (2017). Neopeptide Analyser: A 703
software tool for neopeptide discovery in proteomics data. Wellcome Open Research, 704
2(May), 1–9. https://doi.org/10.12688/wellcomeopenres.11275.1 705
Rigbolt, K. T. G., Vanselow, J. T., & Blagoev, B. (2011). GProX, a user-friendly platform for 706
bioinformatics analysis and visualization of quantitative proteomics data. Molecular and 707
Cellular Proteomics, 10(8), 1–10. https://doi.org/10.1074/mcp.O110.007450 708
Ritty, T. M., Ditsios, K., & Starcher, B. C. (2002). Distribution of the elastic fiber and 709
associated proteins in flexor tendon reflects function. Anatomical Record, 268(4), 430–710
440. https://doi.org/10.1002/ar.10175 711
Russo, V., Mauro, A., Martelli, A., Di Giacinto, O., Di Marcantonio, L., Nardinocchi, D., 712
Berardinelli, P., & Barboni, B. (2015). Cellular and molecular maturation in fetal and 713
adult ovine calcaneal tendons. Journal of Anatomy, 226(2), 126–142. 714
https://doi.org/10.1111/joa.12269 715
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
35
Sensini, A., Gualandi, C., Focarete, M., Belcari, J., Zucchelli, A., Boyle, L., Reilly, G., Kao, 716
A., Tozzi, G., & Cristofolini, L. (2019). Multiscale hierarchical bioresorbable scaffolds 717
for the regeneration of tendons and ligaments. Biofabrication, 11(3), 035026. 718
Spiesz, E. M., Thorpe, C. T., Chaudhry, S., Riley, G. P., Birch, H. L., Clegg, P. D., & Screen, 719
H. R. C. (2015). Tendon extracellular matrix damage, degradation and inflammation in 720
response to in vitro overload exercise. Journal of Orthopaedic Research, 33(6), 889–721
897. https://doi.org/10.1002/jor.22879 722
Stanley, R. L., Edwards, L. J., Goodship, A. E., Firth, E. C., & Patterson-Kane, J. C. (2008). 723
Effects of exercise on tenocyte cellularity and tenocyte nuclear morphology in immature 724
and mature equine digital tendons. Equine Veterinary Journal, 40(2), 141–146. 725
https://doi.org/10.2746/042516408X266097 726
Thorpe, C. T., Chaudhry, S., Lei, I. I., Varone, A., Riley, G. P., Birch, H. L., Clegg, P. D., & 727
Screen, H. R. C. (2015). Tendon overload results in alterations in cell shape and 728
increased markers of inflammation and matrix degradation. Scandinavian Journal of 729
Medicine and Science in Sports, 25(4), e381–e391. https://doi.org/10.1111/sms.12333 730
Thorpe, C. T., & Screen, H. R. C. (2016). Tendon structure and composition. In Advances in 731
Experimental Medicine and Biology (Vol. 920). https://doi.org/10.1007/978-3-319-732
33943-6 733
Thorpe, C T, Udeze, C. P., Birch, H. L., Clegg, P. D., & Screen, H. R. C. (2012). 734
Specialization of Tendon Mechanical Properties Results From Interfascicular 735
Differences. Journal of The Royal Society Interface, 9(76), 3108–3117. 736
Thorpe, Chavaunne T., Godinho, M. S. C., Riley, G. P., Birch, H. L., Clegg, P. D., & Screen, 737
H. R. C. (2015). The interfascicular matrix enables fascicle sliding and recovery in 738
tendon, and behaves more elastically in energy storing tendons. Journal of the 739
Mechanical Behavior of Biomedical Materials, 52, 85–94. 740
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
36
https://doi.org/10.1016/j.jmbbm.2015.04.009 741
Thorpe, Chavaunne T., Karunaseelan, K. J., Ng Chieng Hin, J., Riley, G. P., Birch, H. L., 742
Clegg, P. D., & Screen, H. R. C. (2016). Distribution of proteins within different 743
compartments of tendon varies according to tendon type. Journal of Anatomy, 229(3), 744
450–458. https://doi.org/10.1111/joa.12485 745
Thorpe, Chavaunne T., Peffers, M. J., Simpson, D., Halliwell, E., Screen, H. R. C., & Clegg, 746
P. D. (2016). Anatomical heterogeneity of tendon: Fascicular and interfascicular tendon 747
compartments have distinct proteomic composition. Scientific Reports, 6(February), 1–748
12. https://doi.org/10.1038/srep20455 749
Thorpe, Chavaunne T., Riley, G. P., Birch, H. L., Clegg, P. D., & Screen, H. R. C. (2016). 750
Fascicles and the interfascicular matrix show adaptation for fatigue resistance in energy 751
storing tendons. Acta Biomaterialia, 42, 308–315. 752
https://doi.org/10.1016/j.actbio.2016.06.012 753
Thorpe, Chavaunne T., Streeter, I., Pinchbeck, G. L., Goodship, A. E., Clegg, P. D., & Birch, 754
H. L. (2010). Aspartic acid racemization and collagen degradation markers reveal an 755
accumulation of damage in tendon collagen that is enhanced with aging. Journal of 756
Biological Chemistry, 285(21), 15674–15681. https://doi.org/10.1074/jbc.M109.077503 757
Thorpe, Chavaunne T., Udeze, C. P., Birch, H. L., Clegg, P. D., & Screen, H. R. C. (2013). 758
Capacity for sliding between tendon fascicles decreases with ageing in injury prone 759
equine tendons: A possible mechanism for age-related tendinopathy? European Cells 760
and Materials, 25(0), 48–60. 761
Watts, A. E., Millar, N. L., Platt, J., Kitson, S. M., Akbar, M., Rech, R., Griffin, J., Pool, R., 762
Hughes, T., McInnes, I. B., & Gilchrist, D. S. (2017). MicroRNA29a Treatment 763
Improves Early Tendon Injury. Molecular Therapy, 25(10), 2415–2426. 764
https://doi.org/10.1016/j.ymthe.2017.07.015 765
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
37
Zamboulis, D. E., Senior, J. M., Clegg, P. D., Gallagher, J. A., Carter, S. D., & Milner, P. I. 766
(2013). Distribution of purinergic P2X receptors in the equine digit, cervical spinal cord 767
and dorsal root ganglia. Purinergic Signalling, 9(3), 383–393. 768
https://doi.org/10.1007/s11302-013-9356-5 769
770
771
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
38
Supplementary data 772
Supplementary Figure 1. Tendon structure and graphical abstract for biomechanical testing. 773
Supplementary Figure 2. Scoring of histologic variables for the matrix and fibre phases in the 774
SDFT and CDET through postnatal development. 775
Supplementary Figure 3. Scoring of ELN staining for the matrix and fibre phases in the 776
SDFT and CDET through postnatal development. 777
Supplementary Figure 4. Classification of SDFT matrix and fibre phase identified proteins 778
and differentially abundant proteins according to their associated location. 779
Supplementary Figure 5. Relative mRNA expression of major ECM genes in whole tissue 780
SDFT and CDET through postnatal development. 781
Supplementary Table 1. Histologic variables used in the H&E scoring of the SDFT and 782
CDET sections and the analysis method and reporting criteria adopted. 783
Supplementary Table 2. Gene primer sequences used in relative mRNA expression analysis. 784
Supplementary Table 3. Samples used for analysis along with statistical test used for analysis. 785
Supplementary Table 4. Collagens and proteoglycans identified in SDFT matrix and fibre 786
phases. 787
788
789
790
791
792
793
794
795
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
39
796 Supplementary Figure 1. Tendon structure and graphical abstract for biomechanical 797
testing. (a) Tendon structure (adapted from Spiesz et al. 2015)(Spiesz et al., 2015). (b) H&E 798
section of fibre and matrix phase and schematic of fibre and matrix phase dissection and 799
biomechanical testing. 800
801
802
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
40
803 Supplementary Figure 2. Scoring of histologic variables for the matrix and fibre phases 804
in the SDFT and CDET through postnatal development. * significant difference between 805
tendons, a-f significant difference between age groups. Error bars depict standard deviation. 806
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
41
807
808
809 Supplementary Figure 3. Scoring of ELN staining for the matrix and fibre phases in the 810
SDFT and CDET through postnatal development. Error bars depict standard deviation. 811
812
813
814
815
Supplementary Figure 4. Classification of SDFT matrix and fibre phase identified 816
proteins and differentially abundant proteins (p<0.05, fold change≥2) according to their 817
associated location. 818
819
820
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
42
821
Supplementary Figure 5. Relative mRNA expression of major ECM genes in whole 822
tissue SDFT and CDET through postnatal development. * significant difference between 823
tendons, a-e significant difference between age groups. Error bars depict standard deviation. 824
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
43
Supplementary Table 1. Histologic variables used in the H&E scoring of the SDFT and 825
CDET sections and the analysis method and reporting criteria adopted. When software 826
was adopted to acquire a parameter, the software is additionally reported. “Scored” is used to 827
denote parameters analysed by blinded investigators. 828
Histologic variable Method Criteria
Fibre phase
Cellularity measured (TissueFaxs) 0 – 3, fewer - more
Shape of tendon cells scored 0 – 3, elongated to rounded
Organisation of collagen fibres scored 0 – 3, linear to non-linear
Crimp angle measured (PhotoShop) 0 – 3, smaller to larger
Matrix phase
Percentage of matrix phase measured (TissueFaxs) 0 – 3, lower to higher
Matrix phase width measured (TissueFaxs) 0 – 3, smaller to larger
Cellularity measured (TissueFaxs) 0 – 3, fewer - more
829
830
831
832
833
834
835
836
837
838
839
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
44
Supplementary Table 2. Gene primer sequences used in relative mRNA expression 840
analysis. 841
Gene Primer sequence
DCN F: CATCCAGGTTGTCTACCTTCATAACA
R: CCAGGTGGGCAGAAGTCATT
FMOD F: CTTGGCTCCAGACCCTGAAA
R: TGCCCCTCGCGTCAGA
BGN F: TCACCTTCCAGCCCCTAGAGT
R: AGAAGCAGCCCCTCCTCAA
COMP F: GGTGCGGCTGCTATGGAA
R: CCAGCTCAGGGCCCTCAT
COL1A1 F: GACTGGCAACCTCAAGAAGG
R: CAATATCCAAGGGAGCCACA
COL1A2 F: GCACATGCCGTGACTTGAGA
R: CATCCATAGTGCATCCTTGATTAGG
COL3A1 F: ACGCAAGGCCGTGAGACTA
R: TGATCAGGACCACCAACATCA
TGFB1 F: CCCTGCCCCTACATTTGGA
R: CGGGTTGTGCTGGTTGTACA
GAPDH F: GCATCGTGGAGGGACTCA
R: GCCACATCTTCCCAGAGG
842
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
45
Supplementary Table 3. Samples used for analysis along with statistical test used for analysis. n numbers represent biological replicates. 843 Analysis Tendon Foetus 0 days 0-1 month 3-6 months 1-2 years Statistical analysis
Biomechanics SDFT fibre n=4 n=4 n=3 n=4 n=4 Two-way ANOVA. Outliers < or >
mean 2xSD were removed. The
average of 4-7 technical replicates was
used (depending on sample availability).
SDFT matrix n=4 n=4 n=3 n=4 n=4
CDET fibre n=4 n=4 n=3 n=4 n=4
SDFT matrix n=3 n=4 n=3 n=4 n=4
Histology and Immunohistochemistry SDFT n=3 n=3 n=3 (0-1 year) n=4 (hist.), 3 (IHC) Kruskal-Wallis, Rank Sum Test
CDET n=3 n=3 n=3 (0-1 year) n=4 (hist.), 3 (IHC)
Elastin quantification SDFT n=3 n=3 n=3 (0-1 year) n=3 Two-way ANOVA. The average of 2
technical replicates was used. CDET n=3 n=3 n=3 (0-1 year) n=3
Proteomics SDFT fibre n=3 n=4 n=3 n=4 n=4 Differentially abundant proteins –
PEAKS Q
SDFT matrix n=4 n=4 n=3 n=4 n=4
Differential total neopeptide abundance
– One-way ANOVA, Benjamini-
Hochberg correction
Relative mRNA expression SDFT - n=4 n=3 n=4 n=4 Two-way ANOVA
CDET - n=4 n=3 n=4 n=4
844
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
46
Supplementary Table 4. Collagens and proteoglycans identified in SDFT matrix and 845
fibre phases (1% FDR, protein -10lgP >20, and ≥2 unique peptides). 846
Collagens Matrix Fibre Proteoglycans Matrix Fibre
COL1A1 + + ACAN + +
COL1A2 + + ASPN + +
COL2A1 + + BGN + +
COL3A1 + + CHAD - +
COL4A1 + - DCN + +
COL4A2 + - FMOD + +
COL4A3 - + HAPLN1 + +
COL4A6 + - HSPG2 + +
COL5A1 + + KERA + +
COL5A2 + + LUM + +
COL5A3 + - OGN + +
COL6A1 + + PRELP + +
COL6A2 + + VCAN + -
COL6A3 + +
COL8A1 + -
COL11A1 + +
COL12A1 + +
COL14A1 + +
COL15A1 + +
COL17A1 - +
COL18A1 +
COL21A1 + +
COL28A1 +
847
848
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
.CC-BY 4.0 International licensemade available under a(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted April 24, 2020. ; https://doi.org/10.1101/2020.04.23.058081doi: bioRxiv preprint
Recommended