Genetic approaches to identify pathological limitations in aortic smooth muscle contraction

MSIght: A Modular Platform for Improved Confidence in Global, Untargeted Mass Spectrometry Imaging Annotation

Mass spectrometry imaging (MSI) has gained popularity in clinical analyses due to its high sensitivity, specificity, and throughput. However, global profiling experiments are often still restricted to LC-MS/MS analyses that lack spatial localization due to low-throughput methods for on-tissue peptide identification and confirmation. Additionally, the integration of parallel LC-MS/MS peptide confirmation, as well as histological stains for accurate mapping of identifications, presents a large bottleneck for data analysis, limiting throughput for untargeted profiling experiments. Here, we present a novel platform, termed MSIght, which automates the integration of these multiple modalities into an accessible and modular platform. Histological stains of tissue sections are coregistered to their respective MSI data sets to improve spatial localization and resolution of identified peptides. MS/MS peptide identifications via untargeted LC-MS/MS are used to confirm putative MSI identifications, thus generating MS images with greater confidence in a high-throughput, global manner. This platform has the potential to enable large-scale clinical cohorts to utilize MSI in the future for global proteomic profiling that uncovers novel biomarkers in a spatially resolved manner, thus widely expanding the utility of MSI in clinical discovery.

Shared and distinct pathways and networks genetically linked to coronary artery disease between human and mouse

Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.

Shared and distinct pathways and networks genetically linked to coronary artery disease between human and mouse

Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.

Genetic Profile in Genes Associated with Sports Injuries in Elite Endurance Athletes

Injuries are a complex trait that can stem from the interaction of several genes. The aim of this research was to examine the relationship between muscle performance-related genes and overuse injury risk in elite endurance athletes, and to examine the feasibility of determining a total genotype score that significantly correlates with injury. A cohort of 100 elite endurance athletes (50 male and 50 female) was selected. AMPD1 (rs17602729), ACE (rs4646994), ACTN3 (rs1815739), CKM (rs8111989) and MLCK ([rs2849757] and [rs2700352]) polymorphisms were genotyped by using real-time polymerase chain reaction (real time-PCR). Injury characteristics during the athletic season were classified following the Consensus Statement for injuries evaluation. The mean total genotype score (TGS) in non-injured athletes (68.263±13.197 arbitrary units [a.u.]) was different from that of injured athletes (50.037±17.293 a.u., p<0.001). The distribution of allelic frequencies in the AMPD1 polymorphism was also different between non-injured and injured athletes (p<0.001). There was a TGS cut-off point (59.085 a.u.) to discriminate non-injured from injured athletes with an odds ratio of 7.400 (95% CI 2.548-21.495, p<0.001). TGS analysis appears to correlate with elite endurance athletes at higher risk for injury. Further study may help to develop this as one potential tool to help predict injury risk in this population.

Genetics and sports performance: the present and future in the identification of talent for sports based on DNA testing

The impact of genetics on physiology and sports performance is one of the most debated research aspects in sports sciences. Nearly 200 genetic polymorphisms have been found to influence sports performance traits, and over 20 polymorphisms may condition the status of the elite athlete. However, with the current evidence, it is certainly too early a stage to determine how to use genotyping as a tool for predicting exercise/sports performance or improving current methods of training. Research on this topic presents methodological limitations such as the lack of measurement of valid exercise performance phenotypes that make the study results difficult to interpret. Additionally, many studies present an insufficient cohort of athletes, or their classification as elite is dubious, which may introduce expectancy effects. Finally, the assessment of a progressively higher number of polymorphisms in the studies and the introduction of new analysis tools, such as the total genotype score (TGS) and genome-wide association studies (GWAS), have produced a considerable advance in the power of the analyses and a change from the study of single variants to determine pathways and systems associated with performance. The purpose of the present study was to comprehensively review evidence on the impact of genetics on endurance- and power-based exercise performance to clearly determine the potential utility of genotyping for detecting sports talent, enhancing training, or preventing exercise-related injuries, and to present an overview of recent research that has attempted to correct the methodological issues found in previous investigations.

Cryo-EM structure of the inhibited (10S) form of myosin II

Myosin II is the motor protein that enables muscle cells to contract and nonmuscle cells to move and change shape1. The molecule has two identical heads attached to an elongated tail, and can exist in two conformations: 10S and 6S, named for their sedimentation coefficients2,3. The 6S conformation has an extended tail and assembles into polymeric filaments, which pull on actin filaments to generate force and motion. In 10S myosin, the tail is folded into three segments and the heads bend back and interact with each other and the tail3-7, creating a compact conformation in which ATPase activity, actin activation and filament assembly are all highly inhibited7,8. This switched-off structure appears to function as a key energy-conserving storage molecule in muscle and nonmuscle cells9-12, which can be activated to form functional filaments as needed13-but the mechanism of its inhibition is not understood. Here we have solved the structure of smooth muscle 10S myosin by cryo-electron microscopy with sufficient resolution to enable improved understanding of the function of the head and tail regions of the molecule and of the key intramolecular contacts that cause inhibition. Our results suggest an atomic model for the off state of myosin II, for its activation and unfolding by phosphorylation, and for understanding the clustering of disease-causing mutations near sites of intramolecular interaction.

Numerical knockouts-In silico assessment of factors predisposing to thoracic aortic aneurysms

Myriad risk factors–including uncontrolled hypertension, aging, and diverse genetic mutations–contribute to the development and enlargement of thoracic aortic aneurysms. Detailed analyses of clinical data and longitudinal studies of murine models continue to provide insight into the natural history of these potentially lethal conditions. Yet, because of the co-existence of multiple risk factors in most cases, it has been difficult to isolate individual effects of the many different factors or to understand how they act in combination. In this paper, we use a data-informed computational model of the initiation and progression of thoracic aortic aneurysms to contrast key predisposing risk factors both in isolation and in combination; these factors include localized losses of elastic fiber integrity, aberrant collagen remodeling, reduced smooth muscle contractility, and dysfunctional mechanosensing or mechanoregulation of extracellular matrix along with superimposed hypertension and aortic aging. In most cases, mild-to-severe localized losses in cellular function or matrix integrity give rise to varying degrees of local dilatations of the thoracic aorta, with enlargement typically exacerbated in cases wherein predisposing risk factors co-exist. The simulations suggest, for the first time, that effects of compromised smooth muscle contractility are more important in terms of dysfunctional mechanosensing and mechanoregulation of matrix than in vessel-level control of diameter and, furthermore, that dysfunctional mechanobiological control can yield lesions comparable to those in cases of compromised elastic fiber integrity. Particularly concerning, therefore, is that loss of constituents such as fibrillin-1, as in Marfan syndrome, can compromise both elastic fiber integrity and mechanosensing.

Aneurysms are local dilatations of the arterial wall that are responsible for significant disability and death. Detailed analyses of clinical data continue to provide insight into the natural history of these potentially lethal conditions, with myriad risk factors–including uncontrolled hypertension, aging, and diverse genetic mutations–contributing to their development and enlargement. Yet, because of the co-existence of these risk factors in most cases, it has been difficult to isolate individual effects or to understand how they act in combination. In this paper, we use a computational model of the initiation and progression of thoracic aortic aneurysms to contrast key predisposing factors both in isolation and in combination as well as with superimposed hypertension and aging. The present study recovers many findings from mouse models but with new and important observations that promise to guide in vivo and ex vivo studies as we seek to understand and eventually better treat these complex, multi-factorial lesions, with data-informed patient-specific computations eventually the way forward.

The dominant protein phosphatase PP1c isoform in smooth muscle cells, PP1cβ, is essential for smooth muscle contraction

Contractile force development of smooth muscle is controlled by balanced kinase and phosphatase activities toward the myosin regulatory light chain (RLC). Numerous biochemical and pharmacological studies have investigated the specificity and regulatory activity of smooth muscle myosin light-chain phosphatase (MLCP) bound to myosin filaments and comprised of the regulatory myosin phosphatase target subunit 1 (MYPT1) and catalytic protein phosphatase 1cβ (PP1cβ) subunits. Recent physiological and biochemical evidence obtained with smooth muscle tissues from a conditional MYPT1 knockout suggests that a soluble, MYPT1-unbound form of PP1cβ may additionally contribute to myosin RLC dephosphorylation and relaxation of smooth muscle. Using a combination of isoelectric focusing and isoform-specific immunoblotting, we found here that more than 90% of the total PP1c in mouse smooth muscles is the β isoform. Moreover, conditional knockout of PP1cα or PP1cγ in adult smooth muscles did not result in an apparent phenotype in mice up to 6 months of age and did not affect smooth muscle contractions ex vivo In contrast, smooth muscle-specific conditional PP1cβ knockout decreased contractile force development in bladder, ileal, and aortic tissues and reduced mouse survival. Bladder smooth muscle tissue from WT mice was selectively permeabilized to remove soluble PP1cβ to measure contributions of total (α-toxin treatment) and myosin-bound (Triton X-100 treatment) phosphatase activities toward phosphorylated RLC in myofilaments. Triton X-100 reduced PP1cβ content by 60% and the rate of RLC dephosphorylation by 2-fold. These results are consistent with the selective dephosphorylation of RLC by both MYPT1-bound and -unbound PP1cβ forms in smooth muscle.