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The Pathophysiology of Cardiac Hypertrophy and Heart Failure

William E. Stansfield MD , ... Monte S. Willis MD, PhD , in Cellular and Molecular Pathobiology of Cardiovascular Disease, 2014

Physiologic Hypertrophy

Hypertrophy is derived from the Greek hyper, meaning over, and trophy, meaning growth. It is widely believed to be an adaptive response to increased workload. By undergoing hypertrophy, ventricular wall stress remains constant at higher intraventricular pressures (LaPlace's law). Since cardiomyocytes make up 80–85% of the ventricular volume and are largely thought to be terminally differentiated, the bulk of cardiac hypertrophy results from cardiomyocyte growth (i.e. increase in size). From both clinical and mechanistic standpoints, two fundamental types of cardiac hypertrophy occur: physiologic and pathologic.

Physiologic hypertrophy occurs in very limited circumstances. The most dramatic example is postnatal, or maturational, where the heart grows more than twofold in size. Although some cardiomyocytes become binucleate, most growth results from an increase in cardiomyocyte length and diameter. ²³ Ventricular hypertrophy observed in pregnant women and professional endurance athletes results in more limited growth. Typical changes are only about a 10–20% increase in size compared to age-matched, sedentary, non-pregnant controls. ^24,25

Ventricular Function

The most important characteristic of physiologic hypertrophy, compared with pathologic hypertrophy, is that ventricular function remains normal or even improved, rather than impaired. Both systolic and diastolic functions are normal or enhanced in both athletes and pregnancy when measured by echocardiogram. In further contrast to pathologic hypertrophy, both states are fully reversible. Post-partum women undergo complete mass regression within 8 weeks, and athletes regress even faster, losing most additional mass within a few weeks of deconditioning.

Angiogenesis, Fibrosis, Energy Substrates, and Gene Activation

Critical cellular and molecular events further separate physiologic and pathologic hypertrophy. Angiogenesis is significantly increased in the myocardium during exercise training, as measured by coronary blood flow capacity, coronary artery diameter, and capillary density. Pathologic models are associated with increased fibroblast activity and fibrosis, while physiologic hypertrophy is associated with unchanged levels of fibroblast activity and collagen deposition. In mitochondria, fatty acid oxidation (FAO) accounts for 80–85% of the energy production in the adult cardiomyocyte. In pathologic hypertrophy, there is increased utilization of less efficient glycolytic pathways. In physiologic hypertrophy, the ratio of FAO to glycolysis is preserved. At the gene expression level, pathologic hypertrophy models classically demonstrate induction of a fetal gene expression program including atrial natriuretic factor (ANF), brain natriuretic peptide (BNP), skeletal muscle α-1-actin, (SMα1actin) and β-myosin heavy chain (β-MHC) – all of which are absent in exercise models of hypertrophy.

Thyroid Hormone

The role of thyroid hormone tri-iodothyronine (T3) on physiologic growth is best understood in the context of postnatal cardiac growth. Within a few weeks after birth, T3 levels spike 2000-fold, and then fall back down by the third week. ²⁶ Rodent studies demonstrate that T3 regulates the perinatal change in transcription from β-MHC to α-MHC. ²⁷ T3 additionally increases the expression of SERCA (sarcoplasmic/endoplasmic reticulum calcium ATPase-2, critical for maintaining Ca⁺⁺ concentrations in the sarcoplasmic reticulum), the β1 adrenergic receptor, cardiac troponin I (cTNI), atrial natriuretic factor (ANF), sodium/calcium exchanger (NCX), thyroid receptor alpha (TRα1) and adenylyl cyclase subtypes. ²⁸ Given this array of proteins whose function enhances cardiac performance, it is logical that T3 stimulation of cardiomyocytes can result in enhanced cardiac performance.

Insulin

Insulin acts by binding to the tyrosine kinase insulin receptor (IR), which ultimately activates the phosphatidylinositol 3'-kinase–protein kinase B (PI3K-AKT) signaling pathway. Cardiac specific IR knockout mice show smaller hearts with smaller individual cardiomyocyte volumes, indicating that physiologic hypertrophy is inhibited. ²⁹ When challenged with aortic constriction, however, these mice are more prone to the development of pathologic hypertrophy. ³⁰ In short, the insulin-signaling pathway is essential for normal cardiac growth, and its absence may promote or enable pathologic hypertrophy.

Insulin-like Growth Factor 1

Insulin-like growth factor 1 (IGF1) has roles in both systemic and organ-specific regulatory mechanisms. IGF1 binds to the insulin receptor (IR) and the IGF1 receptor (IGF1R). IGF1R is a transmembrane tyrosine kinase receptor that activates PI3K-AKT-phosphoinositide-dependent protein kinase 1 (PDK1) and subsequently glycogen synthase kinase 3β (GSK3b). IGF1 and IGF1R knockout mice have severe growth retardation and die at birth. ³¹ IGF1 transgenic mice, in which IGF1 is linked to the α-MHC or SM-α-1-actin promoters, show early development of physiologic hypertrophy, but over time the phenotype becomes pathologic, with development of fibrosis and decreased function. ³² Transgenic overexpression of IGF1R using the α-MHC promoter results in development of physiologic hypertrophy without subsequent development of pathology. ³³ Conversely, IGF1R conditional deletion does not affect cardiac growth, but does make mice resistant to exercise-induced hypertrophy. ³⁴

Mechanotransduction

Mechanotransduction is a well-known phenomenon in the cardiomyocyte in which physical contacts are converted into intracellular signals by transmembrane proteins. One stretch receptor expressed by all cells (including myocytes) is the transient receptor potential channel (TRPC). Two subtypes of this receptor – TRPC1 and TRPC6 – are each activated by stretching and are overexpressed in hypertrophy. When knocked out, mice are more resistant to pathologic hypertrophic stimuli. ³⁵ Integrins are another class of transmembrane protein that transmit stretch-related changes in the extracellular matrix through an intracytoplasmic tail. This signals intracellular focal adhesion complexes that include focal adhesion kinase (FAK) and integrin-linked kinase (ILK). These kinases then phosphorylate and activate RHO GTPases, PI3K, and protein kinase C (PKC). Cardiac-specific ablation of the intracytoplasmic integrin signaling tail exacerbates pressure-overload-induced hypertrophy. ³⁶ Within the cardiomyocyte, numerous proteins at the Z-line are involved in stretch sensing including: muscle LIM protein, ³⁷ myopalladin, palladin, ankyrin, and cardiac ankyrin repeat domain protein (CARP). Of these, muscle LIM protein and CARP have known associations with hypertrophy. CARP overexpression transgene is resistant to the development of isoproterenol and pressure-overload-induced hypertrophy. ³⁸ Titin is a protein that spans the length of the sarcomere, from Z-line to Z-line, with over 20 known ligands, many of which are believed to be stretch receptors, yet its precise relationship with hypertrophy remains to be explored.

Intracellular Pathways

PI3K

PI3K is one of the common effectors of insulin, insulin-like growth factor, and integrin signaling pathways (Fig. 4.3). Overexpression of the catalytic subunit of PI3K, p110α, in mouse hearts promotes physiologic hypertrophy. ³⁹ Conversely, overexpression of a dominant negative form of p110α results in atrophy. Phosphatase and tensin homolog (PTEN) is a lipid phosphatase that acts to inhibit phosphatidylinositol 3,4,5 triphosphate (PIP3). Cardiac-specific PTEN deletion has also been shown to promote cardiac growth. ⁴⁰

FIGURE 4.3. Intracellular signaling pathways. Intracellular signaling pathways involved in pathological and physiologic hypertrophy. Activation of a Gα_q/11 G-protein coupled receptor (Gα_q/11) leads to activation of the small GTP-binding proteins, Ras and Rho, which promote pathological hypertrophy through activation of the mitogen-activated protein kinase (MAPK) signaling cascade. Rho also activates Rho kinase (ROCK), another activator of pathologic hypertrophy. Activation of a Gα_q/11 coupled receptor additionally activates phospholipase-Cβ (PLCβ), resulting in inosital-1,4,5-trisphosphate (IP3) and diacylglycerol (DAG) production. IP3 binds to an IP3 receptor on the sarcoplasmic reticulum stimulating calcium release. Calcium and DAG activate protein kinase Cα (PKCα), which promotes pathological hypertrophy. Many forms of hypertrophic stimuli increase the amount of intracellular calcium, leading to the activation of the protein phosphatase, calcineurin. Activated calcineurin de-phosphorylates the nuclear factor of activated T-cells (NFAT), allowing NFAT to enter the nucleus, interact with GATA4 and myocyte enhancer factor-2 (MEF2) leading to increased protein synthesis and pathological hypertrophy. Glycogen synthase kinase-3β (GSK-3β) can phosphorylate and thereby inhibit NFAT nuclear translocation. Stimulation of the insulin-like growth factor 1 receptor activates phosphatidylinositide 3-kinase (PI3K), which phosphorylates and activates Akt to promote physiologic hypertrophy. Akt further activates the mammalian target of rapamycin (mTOR) and inhibits GSK-3β.

AKT

AKT, also known as protein kinase B, is activated by 3-phosphoinositide-dependent protein kinase-1 (PDK1), another kinase recruited to the cell membrane by PIP3 synthesis. PDK1 inactivation reduces cardiomyocyte volume and heart mass. Similarly, Akt null mice are resistant to physiologic hypertrophy in response to swimming. Constitutively active Akt1 mutant mice initially develop physiologic LVH, although pathologic conversion occurs over time. Similar effects are observed in a membrane-localized mutant of Akt1. By comparison, nuclear-targeted Akt1 results in hyperplasia without hypertrophy. One of the mechanisms of AKT is to promote protein translation by inhibiting glycogen synthase kinase 3-β (GSK3β), itself a negative regulator of protein translation. Mouse overexpression models of GSK3β fail to hypertrophy in the post-natal period and die shortly thereafter from heart failure. ⁴¹ Lastly, AKT shifts the balance of protein turnover to anabolism by phosphorylating and inactivating the pro-catabolic transcription factor forkhead box protein 03 (FOX03). This prevents transcription of the pro-catabolites ubiquitin ligase atrogin-1 and muscle-specific RING finger protein-1 (MURF1). ^42,43 Altogether, AKT appears to promote hypertrophic growth of the heart; the timing, duration, and precise nature of the action determine if this is ultimately beneficial or pathologic.

mTOR

The mammalian target of rapamycin (mTOR) regulates adaptive growth of the heart at the level of mRNA translation. mTOR and regulatory associated protein of mTOR (RAPTOR) combine with other proteins to make up mTOR complex-1 and -2 (mTORC1 and mTORC2). mTORC1 is activated via an AKT-led pathway, as well as by certain amino acids, and is inhibited by 5' adenosine monophosphate-activated protein kinase (AMPK). ⁴⁴ Activated mTORC1 initiates translation activity by directly regulating S6K ribosomal proteins, and by liberating eukaryotic translation initiation factor 4E from its binding protein. ⁴⁴ Experimentally, treatment with rapamycin is effective in reversing hypertrophy produced through Akt overexpression. ⁴⁵ However, blocking the mTOR pathway by overexpression of a dominant negative mTOR is insufficient to inhibit the hypertrophic response in exercised mice. ⁴⁶ In summary, the mTOR pathway is one of several redundant pathways that contribute to the development of physiologic LVH.

C/EBPβ

CCAAT/enhancer binding protein-β (C/EBPβ) is a transcription factor that is commonly associated with regulation of cellular proliferation, but has recently been tied to the regulation of physiologic hypertrophy. ⁴⁷ C/EBPβ is down-regulated during exercise-induced physiologic hypertrophy, but remains constant during pressure-overload-induced pathologic hypertrophy. siRNA silencing of C/EBPβ in rat neonatal cardiomyocytes induces both cardiomyocyte proliferation and hypertrophy. In adult mice, C/EBPβ heterozygotes are resistant to the pathologic effects of pressure overload. Relative to wild-type mice, C/EBPβ heterozygotes have a comparable increase in cardiomyocyte size, but with improved fractional shortening and decreased pulmonary weight (signifying less heart failure). ⁴⁷ C/EBPβ inhibition, as a means of inducing physiologic hypertrophy, represents a potential therapeutic modality for patients with heart failure.

ERK1/2

Extracellular signal related kinases 1/2 (ERK1/2) are kinases activated by extracellular signals that translocate to the nucleus, phosphorylate targets, and initiate transcription. Also called mitogen activated kinase 3/1 (MAPK3/1), these kinases are stimulated by growth factors and stretching. Overexpression of an active mutant ERK1 induces physiologic hypertrophy that is protective from ischemia reperfusion injury. ^48,49 Conversely, inhibition of ERK1/2 leads to increased dilated cardiomyopathy in the face of pressure overload. ⁵⁰ ERK1/2 therefore represents an important aspect of physiologic hypertrophic signaling, both in the response to exercise and in the balance of response to pathologic stresses.

AMPK

5' Adenosine monophosphate-activated protein kinase (AMPK) is a metabolic switch that balances energy supply with metabolic demand. During exercise, activated AMPK increases the available energy supply by stimulating catabolic pathways including fatty acid oxidation, glucose uptake and glycolysis, and shuttering anabolic pathways like fatty acid synthesis and protein transcription. Although similarly named to cyclic AMP-activated protein kinase (protein kinase A), the actions of AMPK are very different and should not be confused. Long-term inhibition of AMPK leads to pathologic hypertrophy and heart failure. ⁵¹ Treatment with a constitutively active mutant or rapamycin restores normal ventricular shape and function. ⁵² AMPK is thus a vital control in maintaining the heart's ability to respond to different stresses, both physiologic and pathologic.

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Genomic Profiling in Bone

Aimy Sebastian , Gabriela G. Loots , in Genetics of Bone Biology and Skeletal Disease (Second Edition), 2018

1.3 Profiling Biomechanical Effects on Bone

Mechanical stimuli, such as vibration, axial loading, and bending regulate bone shape and strength, activate bone formation, and increase BMD. ⁶⁹ To identify genes and signal pathways responsible for mechanical loading-induced bone formation, Zhang et al. ¹⁹ examined the global gene expression changes resulting from joint loading. ¹⁹ Joint loading induces an anabolic response and the authors were interested to determine if ankle loading promotes bone formation in the tibia. Accordingly, the left ankle of 14-week-old C57BL/6 mice was loaded 3 min/day for 3 consecutive days (0.5 N/5 Hz). Bone RNA was collected from the right (control) and left (loaded) tibia at 1 h after the 3rd loading and processed using Agilent microarrays. Using histomorphometry the authors determined that there was a corresponding 10% increase in cross-sectional cortical bone area in response to loading. The microarray comparison identified 242 transcripts upregulated ≥1.2-fold and 199 transcripts downregulated ≤ 0.8-fold in response to ankle loading. A more stringent comparison of genes that changed more than twofold from loading identified a group of 50 transcripts including Mmp3, Has, Mrgpra2a, Thbs3, Timp1, Col3a1, Matn2, Matn4, Cd248, Cspg4, Fosb, Aspn, Cdh13, Aqp1, Moxd1, Anxa8, Atf3, Aebp1, Prrx2, Cma1, Hapln1, Il1rl1 (upregulated); and Btc, Senp6, Lrrc34, Barhl2, Tnfp, Phf20l1, Kirrel3, Crisp1, Npy2r, Txnax, Krt82, Ptgs2, Pax7a, Znf236, Crlf1 (downregulated). ¹⁹

In a more recent study, Mantila Roosa et al. ²⁰ evaluated loading-induced gene expression in rat ulna over a time course of 4 h to 32 days (d) (4 h, 12 h, 1 d, 2d, 4d, 6d, 8d, 12d, 16d, 24d, and 32d). Using Affymetrix microarrays they identified 1051 genes that were differentially expressed in at least one time point, in response to loading. After performing a gene expression clustering they identified six distinct patterns of differential gene expression: an early-response cluster in which the genes were upregulated early but not late in the time course, three matrix-formation (up) clusters that followed the pattern of matrix synthesis, and two matrix-formation (down) clusters that were downregulated during matrix formation. Several chemokines (Ccl2, Ccl7, Cxcl1, Cxcl13), calcium signaling genes (Anxa2, S100a4, S100a10), matrix proteins (Adamts1, Ecm1, Serpina3n, Serpine1, Tfpi2), and AP-1 transcription factors (Fosl1, Junb) were identified as upregulated early on, primarily at 4 h. Mantila Roosa et al. also identified several extracellular matrix genes (upregulated: Alpl, Bglap, Col1a2, Cthrc1, Fn1, Ibsp, Lox, Sparc, Vcan, Bgn, etc.; downregulated: Efemp1, Mmp8, Prelp, Serpinb2, Spon1) and growth factors (upregulated: Fgf14, Pdgfa, Pdgfc, Pdgfrl, Pgf; downregulated: Egf, Fgf1, Fgf7, Fgf23, Fgl2, Hgf) as differentially regulated during matrix formation, in response to loading. Several ion channels and solute carriers were also differentially regulated during matrix formation. Interestingly, several muscle-related genes were identified as downregulated in loaded ulna (Acta1, Dmd, Myocd, Myl1, Myplf, Tnni2, Tnnt3, Tpm2), genes that were also identified as enriched in osteocytes compared to osteoblasts by Paic et al. Other important bone metabolism genes differentially regulated during matrix formation included Vdr, Tgfb1, Tgfb3, Bmp2, Wif1, Wisp1, Pthr1, Sp7, Jund (upregulated genes), Grem1, Bmpr1b, Tgfbr3, Chrdl1, and WNT pathway inhibitors Sost and Sfrp4 (downregulated genes).

While studies by Zhang et al. ¹⁹ and Mantila Roosa et al. ²⁰ identified changes in whole bone transcriptome in response to loading, Wasserman et al. ²¹ studied transcriptional changes specifically in trabecular osteocytes from mouse vertebra subjected to controlled compression loading. Using Affymetrix microarrays they profiled gene expression changes in osteocytes isolated from vertebrae receiving a single 8 N loading dose or repetitive loading compared to osteocytes from sham-loaded vertebral trabecular bone. By this approach, Wasserman et al. identified 287 up- and 52 downregulated genes in response to a single load in osteocytes. Upregulated genes included Wnt5a, Aspn, Igf1, Emilin2, Ccl12, Adamts4, and Adamts1 whereas Olfm3 and Spock2 were identified as downregulated. 1339 genes were differentially regulated (778 up- and 561 downregulated) in osteocytes isolated from vertebra subjected to repetitive loading. Genes upregulated by repetitive loading included Ptn, Vcan, Aspn, Thbs4, Sema3c, Sema3d, Thbs2, Thbs1, Mmp2, Cyr61, Grem1, Fgf18, Grem2, Pdgfd, Wnt5a, and Dmp1 whereas Ltbp1, Muc4, and Apoa5 were downregulated. In summary, Wasserman et al. identified several genes, in particular those encoding extracellular proteins, differentially regulated in osteocytes in response to loading. It is interesting to note that Sost was not detected among the significantly downregulated transcripts though it is generally recognized that mechanical loading downregulates Sost expression in osteocytes. ^70,71

Multiple studies have suggested that mechanical loading differentially increases bone mass in cortical and cancellous sites. In a recent study, Kelly et al. ²² investigated transcriptional changes in cortical and cancellous bone in response to mechanical loading. In this study the left tibia of 10-week-old C57Bl/6 female mice was subjected to a single load and cortical and cancellous bone was collected 3 and 24 h after loading and changes in gene expression were profiled using RNAseq. At 3 h postloading, 43 and 18 genes were found differentially expressed in loaded cortical and cancellous bones, respectively. Genes upregulated in both cortical and cancellous bone included Wnt1, Wnt7b, Timp1, Ptgs2, and Opg. Enriched signaling pathways included WNT signaling in both cortical and cancellous bone and hedgehog signaling in cortical bone only. Apart from Wnt1 and Wnt7b, an increased expression of Wnt10b was also observed at 3 h after a single loading session, in the cortical bone, while Lrp5 was modestly decreased. WNT inhibitors Sost and Dkk1 were found to be downregulated in cancellous bone 3 h after loading, but were not significantly changed in the cortical bone. At 24 h postloading, 58 genes were differentially expressed in cortical and 32 genes in cancellous bone. 12 genes (Ptn, Vcan, Cthrc1, Hapln4, Tubb3, etc.) were commonly changed in both cortical and cancellous bone. Wnt1 and Wnt10b remained upregulated at 24 h postloading in cortical bone. Interestingly, several muscle-related genes (Myh4, Tnnc2, Smpx, Tnnt3, Mylk2, Myoz1, Myom2, Actn3, Myl1, Casq1, Mybpc2, Myh2, Mylpf, Tnni2) were found to be downregulated in cancellous bone at 24 h postloading. It is important to note that several of these muscle-related genes including Tnnc2 and Tnnt3 were also identified by Paic et al. as enriched in osteocytes and by Mantila Roosa et al. as downregulated in the loaded ulna. Kelly et al. also observed that Wnt16, Wnt7b, and Sost were highly expressed in unloaded cortical bone compared to unloaded cancellous bone. High expression of Wnt16 in cortical bone is consistent with the cortical bone phenotype in mice lacking Wnt16. ⁷² Other genes highly expressed in unloaded cortical bone include bone metabolism related genes Postn, Aspn, Mepe, Ostn, and Ptn while genes including Grem1, Kcnj5, and Slc24a5 showed high expression in unloaded cancellous bone. This study highlights the importance of WNT signaling in load induced bone formation and provides novel insights into differential response of cortical and cancellous bone to mechanical loading. Further investigation into the downregulation of muscle-related genes in cancellous bone is required to understand the functions of these genes in bone.

Tissues derived from an organism are highly heterogeneous and the transcriptional profile represents a comprehensive sum of multiple cell-type outputs. A highly specialized signal that comes exclusively from one cell type may be diluted in tissue samples if the surrounding tissues may exhibit the opposite transcriptional effect. Wasserman et al. ²¹ purified osteocytes from loaded bone in an attempt to understand the changes specific to this cell type and identified several differentially regulated genes. However, they failed to recapitulate several known load induced changes in osteocyte transcriptome including downregulation of Sost. Studies by Mantila Roosa et al. ²⁰ and Kelly et al. ²² highlighted the importance of studying loaded induced changes as a function of time; they observed significant differences in the loaded bone transcriptome at different time points. Future studies will have to rely on purifying homogenous populations of cells, similar to the study described in the first section by Paic et al., ¹⁵ from different time points in order to distinguish cell autonomous from noncell autonomous effects and to understand temporal changes.

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Molecular architecture of adherens junctions

Akira Nagafuchi , in Current Opinion in Cell Biology, 2001

Each component of an AJ interacts with the other components to form intricate molecular complexes. α-catenin, especially, binds directly to many proteins, including β-catenin, vinculin, ZO-1, α-actinin and actin [4]. This molecule is also involved in the proper localization of nectin–afadin and the vezatin–myosin-VIIA complexes [12•,17•]. It is likely that the disordered interaction of α-catenin with these partner proteins outside of AJs might severely damage cells. In fact, overexpression of α-catenin binds to cytoplasmic β-catenin and disturbs β-catenin-mediated Wnt signals [21]. To avoid such undesirable reactions, protein expression and the interaction of α-catenin with its partners should be strictly regulated in the cells. It has been reported previously that cadherin is required for a high-level expression of α-catenin, which is post-transcriptionally regulated [22]. We recently demonstrated that a low efficiency of translation combined with unidentified degradation mechanisms maintained a low level of α-catenin protein expression in the absence of cadherins [23•]. We also suggested that the 5′-untranslated sequence of α-catenin is involved in this translational regulation [23•]. Interestingly, overexpression of β-catenin in the absence of cadherins hardly affects the expression level of α-catenin protein. Cadherins as well as β-catenin are required for a high-level expression of α-catenin protein. It is accepted that α-catenin binds directly to β-catenin but not to E-cadherin. The suggestion that cadherins are involved in the translational regulation of α-catenin would provide an attractive hypothesis for explaining the phenomenon of how cadherin molecules regulate the expression level of α-catenin proteins without their direct interaction.

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Shaping Striated Muscles with Ubiquitin Proteasome System in Health and Disease

Karim Hnia , ... Christel Moog-Lutz , in Trends in Molecular Medicine, 2019

DUBs and Shuttle Factors

To date, several DUBs of the ubiquitin specific peptidase (USP) family such as USP2, USP14, USP19, USP25, and USP28 have been identified as UPS regulators in muscle [49], with USP19 being the most intensely studied DUB. USP19 is induced during muscle wasting and may control the levels of certain myofibrillar proteins [50]. The USP25 isoform (USP25m) is restricted to muscular tissues and is upregulated during myogenesis [51]. USP25m interacts with three sarcomeric proteins: actin alpha-1 (ACTN1), FLNC, and myosin-binding protein C1 (MyBPC1) but only MyBPC1 degradation is prevented by overexpression of USP25m (Figure 3B) [52].

The proteasomal shuttle factors, including UBQLN1/2 and RAD23B, have been shown to participate in muscle PQC. Although there are no reported sarcomeric protein targets for UBQLN1, CM-restricted knockout of UBQLN1 accumulated oxidized and ubiquitinated proteins, resulting in late-onset cardiomyopathy and exacerbated myocardial ischemia-reperfusion injury [53]. However, a role of UBQLN2 in the degradation of desmin was recently proposed [54]. When misfolded desmin filaments accumulate in skeletal muscle cells, UBQLN2 binds to the desmin-binding protein (myotubularin, MTM1). The UBQLN2-MTM1 interaction promotes heat shock protein (HSP) recruitment, thereby binding to misfolded desmin, and activates UBQLN2-cargo to shuttle to the proteasome (Figure 3B) [54]. The E3 ligases involved in this cascade remain to be identified.

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Effects of passive heating intervention on muscle hypertrophy and neuromuscular function: A preliminary systematic review with meta-analysis

Patrick Rodrigues , ... Geoffrey M. Minett , in Journal of Thermal Biology, 2020

1 Introduction

The use of thermal therapies involving passive heating has occurred since the time of Hippocrates (Papaioannou et al., 2016). Since then, passive heating has been therapeutically administered as part of various cardiovascular, metabolic, oncological, and other health treatments (Brunt et al., 2016; Habash et al., 2006a; Maley et al., 2019; Pallubinsky et al., 2017). Targeting skeletal muscle, localised heat application is used in post-exercise recovery and the rehabilitation of sports-related soft tissue injury (Naito et al., 2012) as heat-induced effects may protect against damage (McGorm et al., 2018). There is also the potential to use passive heating for its exercise mimetic properties (e.g., a therapeutic strategy that can stimulate comparable physiological benefits to exercise, such as augmented muscle mass and strength), with reports of acute (Littmann and Shields, 2016; Ohno et al., 2010; Uehara et al., 2004), medium-term (Hafen et al., 2019; Racinais et al., 2016), and chronic benefits (Goto et al., 2011; Kodesh and Horowitz, 2010).

Passive heating methods have been used to increase core and/or muscle temperature via different temperature and exposure time, depending on their mechanistic target (e.g., part- or whole-body heating). Hyperthermia is achieved with low-temperature applications (e.g. < 41 °C applied for about 60 min) that increase blood flow and metabolic rates (Habash et al., 2006b), while interventions targeting cellular death (e.g., tumours) via heat-induced protein denaturation require hotter applications (Raaphorst, 1990). A series of molecular events associated with muscle growth also occur during physiological hyperthermia (increased core temperature). Passive heating reportedly changes in gene expression (i.e., upregulated polypeptide 1 myosin, heavy polypeptide 2 myosin and alpha 1 actin (Guo et al., 2016), preventing glucocorticoids-induced muscle atrophy (Tsuchida et al., 2017)), has anti-inflammatory and antioxidant effects (Takeuchi et al., 2014; Vardiman et al., 2015), improves glucose metabolism (Hoekstra et al., 2018), mitochondrial biogenesis (Garramone et al., 1994; Hafen et al., 2018; Touchberry et al., 2012), heat shock protein (HSP) expression (e.g. HSP27, HSP70, HSP72 and HSP90) (Castellani et al., 2016; Ogura et al., 2007) and inhibits skeletal muscle atrophy (Hafen et al., 2019; Hirunsai and Srikuea, 2018; Tamura et al., 2015). Moreover, increases in muscle mass have been reported after one passive heating session (60 min) in animal samples (Littmann and Shields, 2016), suggesting that passive heating can promote cell proliferation and induce muscular hypertrophy (Goto et al., 2004; Naito et al., 2000; Uehara et al., 2004).

If passive heating can stimulate skeletal muscle hypertrophy, it is plausible that passive heating would also increase muscle strength (Kodesh and Horowitz, 2010). Indeed, Goto et al. (2011) demonstrated a ~5.8% increase in human knee extensor isometric maximal voluntary contraction torque after a ten-week local passive heating intervention (8 h/day, 4 days/week). Further, passive heat acclimation has been evidenced to augment skeletal muscle contractility in humans (evoked peak twitch) (Racinais et al., 2016). Despite this potential improvement in muscle strength, it remains unclear whether passive heating may evoke adaptations in both central and peripheral contributions to muscle performance. According to Littmann and Shields (2016), passive heating may serve as an adjunct strategy to trigger systemic stressor to adapt central nervous system responsiveness. An acute passive heating session can increase motor cortical excitability measured via transcranial magnetic stimulation and might be an effective intervention to enhance movement control and learning (Littmann and Shields, 2016). These findings raise further questions concerning the mechanistic underpinnings of passive heating induced neuromuscular adaptations.

Despite the physical and mental benefits derived from regular physical activity, in high-income Western countries, 36.8% of the adult population do not meet the recommended World Health Organization guidelines for physical activity (Guthold et al., 2018; World Health Organization, 2010). As the healthcare cost of age-related chronic diseases rises with ageing population growth, it is logical to explore novel interventions that can supplement the benefits of exercise (Littmann and Shields, 2016). However, while no single therapeutic intervention may offer the physical, physiological and mental benefits of exercise, exercise mimetic strategies have the potential to provide at least some like benefits, especially for sedentary (Fan and Evans, 2017) and clinical population (e.g., post-surgery, people on wheelchair or bed rest) or those experiencing low tolerance to exercise (e.g., the aged, obese, and diseased populations) (Hafen et al., 2018). Passive heating may offer exercise mimetic hypertrophy and neuromuscular adaptations that could resultantly increase the quality of life and decrease healthcare costs (Hunt et al., 2019). Accordingly, this systematic review and meta-analysis aimed to synthesise the evidence on the effects of passive heating on muscle hypertrophy and neuromuscular function.

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Proteomic application in predicting food quality relating to animal welfare. A review

Daniel Mouzo , ... María López-Pedrouso , in Trends in Food Science & Technology, 2020

3 Proteomic approach to monitor beef and milk quality in response to stress

In cattle production, there is an increasing interest in stress control to prevent economic losses and to improve animal welfare. Currently, beef industry investigates the animal rearing and slaughter conditions to achieve a higher beef quality (color, intramuscular fat content or marbling and water holding capacity). It is proven that poor animal production conditions may simultaneously affect both animal welfare and beef quality. Stress can be a result of many factors intrinsic (physiology, age, sex and genotype) and extrinsic (temperature, handling activities, human presence, lairage time, and feed/water deprivation). Among them, the psychological and social aspects are more difficult to control by industry. In bovine livestock, fear is a common stressor caused by handling. Heat stress is especially relevant and it has been proven that leads to physiological stress, causing increases in muscle pH that negatively influence beef quality (Kadim et al., 2004). Another psychological aspect which triggers the fear is the mixture with unfamiliar animals or being isolated (Grandin, 1997; Terlouw et al., 2008). Beyond these common factors, the degree of stress is highly variable depending on the type, the intensity and the period. For all these reasons, stress has a highly complex character and difficult to monitor from an industrial viewpoint. However, the study of the proteome could have a great relevance for search of biomarkers associated with stress as several studies have shown (Table 1).

Table 1. Effect of stress on quality of cattle products and search of protein biomarkers using different proteomic technologies.

Stress sources	Effects of stress	Proteomic sample	Proteomic technologies	Effects on proteome	Protein biomarkers	Reference
Heat stress	Alteration of synthesis and secretion of milk (milk protein and fat)	Bovine mammary epithelial cells	iTRAQ LC-MS/MS Elisa Western Blotting	Effects associated with cell-substrate junction assembly, catabolic processes and metabolic processes	–	Li et al. (2017)
Heat stress (long term)	Inflammatory response (tumor necrosis factor-α interleukin-6)	Blood plasma	2-DE MALDI-TOF/TOF Western Blotting	Alteration of plasma proteins	Keratin, type II cytoskeletal 3-like Protein HP-25 homolog 1 and 2 Hepatitis A virus cellular receptor 1 Transthyretin precursor	Min et al. (2016)
Heat stress	Deterioration of function liver during early lactation contributing to fatty liver disease	Liver biopsia	LC-MS/MS Western Blotting	Changes in oxidative phosphorylation, mitochondrial dysfunction, farnesoid X receptor/retinoid X receptor (FXR/RXR) activation, and the methylmalonyl pathway.	Cytochrome c oxidase subunit 4 isoform 1 Peroxidoxin-3	Skibiel et al. (2018)
Heat stress	The stress increased the concentration of malondialdehyde and cortisol in blood plasma	Subcutaneous adipose tissue	Nano-UPLC-ESI Western Blotting	Differential abundance of 107 proteins in adipose of pregnant cows, affecting Nrf2-mediated oxidative stress response, acute-phase response, and FXR/RXR and LXR/RXR activation	Dual-specificity mitogen-activated protein kinase kinase 1 GST Mu 1 Stress-induced-phosphoprotein 1	Zachut et al. (2017)
Different management systems	Hardest conditions in the mountains induce a higher oxidative stress in the animal	Serum samples	Immunoblotting DIGE MALDI-TOF/TOF	Increased carbonyl content in plasma proteins and higher GPx and SOD activity	FGG protein Complement C3B Complement component C9 precursor Complement C1s subcomplement Serum albumin Paraoxonase Conglutinin Lactate dehydrogenase B Protein AMBP precursor Alpha-2-HS glycoprotein precursor (AHSG Immunoglobulin J chain Selenium dependent glutathione peroxidase	Marco-Ramell et al. (2012)
Transportation, weaning and commingling	Increased incidence of bacterial and viral pneumonia detected in epithelial lining fluid of the lungs	Epithelial lining fluid of the lungs	2-DE LC-MS/MS Immunoblotting	Different abundance in eleven proteins which could be used as biomarkers for stress-associated disease susceptibility	Annexin A1 and A5 Odorant-binding protein Isocitrate dehydrogenase Fibrinogen Heme-binding protein α-2-HS-glycoprotein α-1-antichymotrypsin Albumin	Mitchell et al. (2008)
Unknown	DFD meats	Longissimus thoracis	2-DE LC-MS/MS MALDI-TOF/TOF	Alteration of structural-contractile proteins and metabolism enzymes	Myosin light chain isoforms Skeletal myosin light chain 2 isoforms Troponin C type 2 Cofilin-2 Triosephosphate isomerase ATP synthase Beta-galactoside alpha-2,6-sialyltransferase	Franco et al., 2015*
Unknown	DFD meats	Bovine loin samples	SDS-PAGE LC-MS/MS	Sarcoplasmic sub-proteome was strongly affected	Actin Phosphoglucomutase-1 Alpha-crystallin B Heat shock protein beta-6 Heat shock protein beta-1	Fuente-Garcia et al., 2019*
Unknown	Dark cutting in meat	Longissimus thoracis	2-DE LC-MS/MS MALDI-TOF/TOF	Changes of upregulation of oxidative myofibril proteins affecting the myosin isoforms	Actin, alpha skeletal muscle ACTA1 Glycogenin 1 Isoform Beta-2 of Protein phosphatase Myomesin-1 Adenylate kinase isoenzyme 1 Peroxiredoxin-1 Desmin Spermine synthase Myosin regulatory light chain 2 Creatine kinase M-type Tropomyosin alpha-1 chain 14–3-3 protein gamma Alpha-crystallin B chain Heat shock 27 kDa protein 1	Mahmood et al., 2018*
Unknown	DFD meats	Longissimus thoracis	2-DE LC-MS/MS MALDI-TOF/TOF	Overall phosphorylation rates changed between DFD and normal meat	Troponin-T F-actin-cappin Small heat proteins	Mato et al., 2019*

Moderate to high cattle stress can lead a defective meat, knowledge as DFD (dark, firm and dry) meats. The main problems of this meat are the tenderness alterations due to higher water holding capacity (WHC), an unappealing darker color and lower microbial stability (Newton & Gill, 1981). In addition, the sensorial quality of DFD meats is below normal ones. The phenomenon occurs because there is a large consumption of muscle glycogen reserves, which produces a great accumulation of lactic acid under stress conditions. This fact provokes an important pH decline, altering the normal acidification process during aging meat. For these reasons, the ultimate pH (measured at 24–48 h) is often higher than 6.0 provoking a scarce protein denaturation and the bound water remain tightly connected. Moreover, the darker color is due to higher intracellular water content, which reflects less light. The myoglobin is not denatured at high pH facilitating an aerobic metabolism at the surface and iron remains in the ferrous state (Miller, 2007). In general, bovine muscle undergo noticeable changes in response to pre-slaughter stress which lead to DFD meats. Proteomics to study stress condition may analyse this type of meats in the discovery of protein biomarkers (Table 1). According to Franco et al. (2015), changes in the proteome between normal and DFD meats were characterised by structural proteins such as myosin light chain isoforms and troponin C type 2. Mahmood, Turchinsky, Paradis, Dixon, and Bruce (2018) also found differences in structural proteins of insoluble fraction analysing meat with pH higher than 5.9 vs. normal meats. These authors suggested that an increased pH as well as a reduced glucidic potential in muscle might be due to the upregulation of oxidative myofibril proteins during the physiological demand, producing changes in myosin isoforms. On the other hand, soluble proteins such as isoform alpha-1 actin, glycogenin-1 and isoform beta-2 of protein phosphatase were differentially more abundant in darker meats with pH higher than 5.9. A sarcoplasmatic subproteomic study using liquid isoelectric focusing (OFFGEL) and mass spectrometry also detected five protein bands significantly different between normal and DFD meats. These bands were identified as actin, phosphoglucomutase-1, alpha-crystallin B, heat shock protein beta-6 and heat shock protein beta-1 (Fuente-Garcia et al., 2019). Furthermore, substantial phosphoproteome changes were detected, resulting in more abundance of phosphoproteins in DFD beef than in normal meat related to structural-contractile, metabolism, electron transport chain, actin polymerization and stress response (Mato et al., 2019).

Stress can also play a negative effect on milk in terms of yield and composition (Pragna et al., 2017; West, 2003). In general, heat stress is one of the major factors which affects both quality and quantity of milk, causing diseases or reducing growth in small ruminants (Berihulay, Abied, He, Jiang, & Ma, 2019). Within dairy cattle, stress undoubtedly is one of the major concerns around the world. Factors such as temperature and relative humidity may result in milk yield reduction and lower quality in relation to fat, protein, casein and lactose content (Bernabucci et al., 2014), because heat stress lead to reduced triacylglycerol lipid production of short and medium chain fatty acids, meanwhile long chain fatty acids are increased. This entails significant changes in physical properties and nutritional value of milk (Liu et al., 2017). Moreover, cows suffering extreme conditions of temperature and humidity produce milk with lower lactose and protein (Garcia, Angeli, Machado, de Cardoso, & Gonzalez, 2015). In the protein fraction, the caseins are the most important in milk entailing around 78% of total protein. A proteomic approach revealed that differentially expressed proteins by heat stress effect are associated with cell-substrate junction assembly and catabolic and metabolic processes, and particularly, synthesis and secretion of milk including milk protein and fat. Regarding caseins, a reduced content of β-casein together with fatty acids were observed under heat stress conditions (Li, Wang, Li, & Wang, 2017). Another relevant tissue, which is greatly affected by heat stress, is the subcutaneous adipose, hence it is interesting for protein biomarkers searching. In this regard, Nrf2-mediated oxidative stress response turned out to be the most affected pathway by seasonal heat stress on dairy cows (Zachut et al., 2017). As mentioned previously, dairy cows are more susceptible to diseases under heat stress conditions. Indeed, bacterial mastitis is the most relevant disease in dairy cows. The intramammary infections lead to a high value of somatic cells (leukocytes and epithelial cells) in milk with respect to normal milk. For this reason, the somatic cells count is evaluated for the detection of cows infected with significant pathogens. It has been reported that somatic cells count in milk was higher in animals under thermal stress (cold and heat stress) due to immune function depression caused by oxidative stress (Hammami, Bormann, M'hamdi, Montaldo, & Gengler, 2013). From a proteomic viewpoint, plasma tumor necrosis factor-α and interleukin-6, two pro-inflammatory protein, were increased in cow blood plasma by long-term heat conditions (Min et al., 2016). Heat stress also has negative consequences on reproductive performance, decreasing the conception rates during summer seasons affecting milk production indirectly (Polsky & von Keyserlingk, 2017). Moreover, cows during early lactation may suffer fatty liver disease provoked by heat stress due to a function liver deterioration. In a proteomic study of liver tissue, the pathways differing between stressed group by cool and heat were identified as oxidative phosphorylation, mitochondrial dysfunction, farnesoid X receptor/retinoid X receptor (FXR/RXR) activation, and the methyl-malonyl pathway (Skibiel, Zachut, do Amaral, Levin, & Dahl, 2018). Thus, the requirements of lactating dairy cattle must be considered in order to increase milk production and quality.

A few proteomic studies have been performed about other stress sources in bovine animals. However, it has been reported that proteomic analysis of cows under different production systems revealed an oxidative stress response in serum samples (Marco-Ramell et al., 2012). The stresses of transportation, weaning and mixing with unfamiliar individuals was studied to prevent/detect bacterial and viral pneumonia in cattle and nine protein were identified as protein biomarkers by 2-DE and LC-MS/MS (Mitchell, Clark, Siwicky, & Caswell, 2008).

Bovines under stress conditions showed meaningful differences on the proteome (Table 1) and a wide range of protein biomarkers were identified. An integrative approach was necessary to analyse them, consequently, a functional enrichment of analysis was performed (Fig. 2). For this, the 29 biomarkers identified in bovine muscle were employed in gene enrichment analysis within the category of biological process. The individual Gene Ontology (GO) terms were ordered by the p-value (red), the percentage of genes (green) and the reference (p = 0.05, blue) are depicted together. The most relevant GO term is "muscle filament sliding" (p < 0.001) which includes actin isoforms, myosin light chain isoforms and troponin C. This term is clearly connected with muscle contraction due to sliding of actin filaments and myosin thick filaments. The second GO term affected significantly was "muscle contraction" which comprises proteins such as actin isoforms, alpha-crystallin B chain, myomesin, myosin light chain isoforms, skeletal myosin light chain isoforms and troponin C. The other GO term, "regulation of muscle contraction", is also related to structural proteins and structure of the myofibrils. Consistently, structural proteins of the sarcomere, such as those mentioned above, are involved in beef tenderization during aging. It has been reported that in DFD meats, a higher pH causes a greater electrostatic repulsion between myofibrillar proteins and less lateral shrinkage (Pearce, Rosenvold, Andersen, & Hopkins, 2011). Obviously, these aspects have a considerable impact on beef tenderness, water holding capacity and color composing beef quality.

Fig. 2. Functional enrichment analysis of proteins using FunRich. Enrichment of biological process from proteins using only the muscle tissue studies marked with asterisk (Table 1).

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