Satellite cells in the growth and maintenance of muscle.

Embryonic skeletal muscle growth is contingent upon a population of somite derived satellite cells, however, the contribution of these cells to early postnatal skeletal muscle growth remains relatively high. As prepubertal postnatal development proceeds, the activity and contribution of satellite cells to skeletal muscle growth diminishes. Eventually, at around puberty, a population of satellite cells escapes terminal commitment, continues to express the paired box transcription factor Pax7, and reside in a quiescent state orbiting the myofiber periphery adjacent to the basal lamina. After adolescence, some satellite cell contributions to muscle maintenance and adaptation occur, however, their necessity is reduced relative to embryonic, early postnatal, and prepubertal growth.

Murine MHC-Deficient Nonobese Diabetic Mice Carrying Human HLA-DQ8 Develop Severe Myocarditis and Myositis in Response to Anti-PD-1 Immune Checkpoint Inhibitor Cancer Therapy.

Myocarditis has emerged as an immune-related adverse event of immune checkpoint inhibitor (ICI) cancer therapy associated with significant mortality. To ensure patients continue to safely benefit from life-saving cancer therapy, an understanding of fundamental immunological phenomena underlying ICI myocarditis is essential. We recently developed the NOD-cMHCI/II-/-.DQ8 mouse model that spontaneously develops myocarditis with lower mortality than observed in previous HLA-DQ8 NOD mouse strains. Our strain was rendered murine MHC class I and II deficient using CRISPR/Cas9 technology, making it a genetically clean platform for dissecting CD4+ T cell-mediated myocarditis in the absence of classically selected CD8+ T cells. These mice are highly susceptible to myocarditis and acute heart failure following anti-PD-1 ICI-induced treatment. Additionally, anti-PD-1 administration accelerates skeletal muscle myositis. Using histology, flow cytometry, adoptive transfers, and RNA sequencing analyses, we performed a thorough characterization of cardiac and skeletal muscle T cells, identifying shared and unique characteristics of both populations. Taken together, this report details a mouse model with features of a rare, but highly lethal clinical presentation of overlapping myocarditis and myositis following ICI therapy. This study sheds light on underlying immunological mechanisms in ICI myocarditis and provides the basis for further detailed analyses of diagnostic and therapeutic strategies.

Automated assembly of molecular mechanisms at scale from text mining and curated databases.

The analysis of omic data depends on machine-readable information about protein interactions, modifications, and activities as found in protein interaction networks, databases of post-translational modifications, and curated models of gene and protein function. These resources typically depend heavily on human curation. Natural language processing systems that read the primary literature have the potential to substantially extend knowledge resources while reducing the burden on human curators. However, machine-reading systems are limited by high error rates and commonly generate fragmentary and redundant information. Here, we describe an approach to precisely assemble molecular mechanisms at scale using multiple natural language processing systems and the Integrated Network and Dynamical Reasoning Assembler (INDRA). INDRA identifies full and partial overlaps in information extracted from published papers and pathway databases, uses predictive models to improve the reliability of machine reading, and thereby assembles individual pieces of information into non-redundant and broadly usable mechanistic knowledge. Using INDRA to create high-quality corpora of causal knowledge we show it is possible to extend protein-protein interaction databases and explain co-dependencies in the Cancer Dependency Map.

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.

Endurance exercise attenuates juvenile irradiation-induced skeletal muscle functional decline and mitochondrial stress.

BACKGROUND: Radiotherapy is commonly used to treat childhood cancers and can have adverse effects on muscle function, but the underlying mechanisms have yet to be fully elucidated. We hypothesized that endurance exercise following radiation treatment would improve skeletal muscle function. METHODS: We utilized the Small Animal Radiation Research Platform (SARRP) to irradiate juvenile male mice with a clinically relevant fractionated dose of 3× (every other day over 5 days) 8.2 Gy X-ray irradiation locally from the knee to footpad region of the right hindlimb. Mice were then singly housed for 1 month in cages equipped with either locked or free-spinning voluntary running wheels. Ex vivo muscle contractile function, RT-qPCR analyses, resting cytosolic and sarcoplasmic reticulum (SR) store Ca2+ levels, mitochondrial reactive oxygen species levels (MitoSOX), and immunohistochemical and biochemical analyses of muscle samples were conducted to assess the muscle pathology and the relative therapeutic impact of voluntary wheel running (VWR). RESULTS: Irradiation reduced fast-twitch extensor digitorum longus (EDL) muscle-specific force by 27% compared to that of non-irradiated mice, while VWR post-irradiation improved muscle-specific force by 37%. Radiation treatment similarly reduced slow-twitch soleus muscle-specific force by 14% compared to that of non-irradiated mice, while VWR post-irradiation improved specific force by 18%. We assessed intracellular Ca2+ regulation, oxidative stress, and mitochondrial homeostasis as potential mechanisms of radiation-induced pathology and exercise-mediated rescue. We found a significant reduction in resting cytosolic Ca2+ concentration following irradiation in sedentary mice. Intriguingly, however, SR Ca2+ store content was increased in myofibers from irradiated mice post-VWR compared to mice that remained sedentary. We observed a 73% elevation in the overall protein oxidization in muscle post-irradiation, while VWR reduced protein nitrosylation by 35% and mitochondrial reactive oxygen species (ROS) production by 50%. Finally, we found that VWR significantly increased the expression of PGC1α at both the transcript and protein levels, consistent with an exercise-dependent increase in mitochondrial biogenesis. CONCLUSIONS: Juvenile irradiation stunted muscle development, disrupted proper Ca2+ handling, damaged mitochondria, and increased oxidative and nitrosative stress, paralleling significant deficits in muscle force production. Exercise mitigated aberrant Ca2+ handling, mitochondrial homeostasis, and increased oxidative and nitrosative stress in a manner that correlated with improved skeletal muscle function after radiation.

Automated Network Assembly of Mechanistic Literature for Informed Evidence Identification to Support Cancer Risk Assessment.

BACKGROUND: Mechanistic data is increasingly used in hazard identification of chemicals. However, the volume of data is large, challenging the efficient identification and clustering of relevant data. OBJECTIVES: We investigated whether evidence identification for hazard assessment can become more efficient and informed through an automated approach that combines machine reading of publications with network visualization tools. METHODS: We chose 13 chemicals that were evaluated by the International Agency for Research on Cancer (IARC) Monographs program incorporating the key characteristics of carcinogens (KCCs) approach. Using established literature search terms for KCCs, we retrieved and analyzed literature using Integrated Network and Dynamical Reasoning Assembler (INDRA). INDRA combines large-scale literature processing with pathway databases and extracts relationships between biomolecules, bioprocesses, and chemicals into statements (e.g., "benzene activates DNA damage"). These statements were subsequently assembled into networks and compared with the KCC evaluation by the IARC, to evaluate the informativeness of our approach. RESULTS: We found, in general, larger networks for those chemicals which the IARC has evaluated the evidence to be strong for KCC induction. Larger networks were not directly linked to publication count, given that we retrieved small networks for several chemicals with little support for KCC activation according to the IARC, despite the significant volume of literature for these specific chemicals. In addition, interpreting networks for genotoxicity and DNA repair showed concordance with the IARC KCC evaluation. DISCUSSION: Our method is an automated approach to condense mechanistic literature into searchable and interpretable networks based on an a priori ontology. The approach is no replacement of expert evaluation but, instead, provides an informed structure for experts to quickly identify which statements are made in which papers and how these could connect. We focused on the KCCs because these are supported by well-described search terms. The method needs to be tested in other frameworks as well to demonstrate its generalizability. https://doi.org/10.1289/EHP9112.

Muscle-specific functional deficits and lifelong fibrosis in response to paediatric radiotherapy and tumour elimination.

BACKGROUND: As paediatric cancer survivors are living into adulthood, they suffer from the age-related, accelerated decline of functional skeletal muscle tissue, termed sarcopenia. With ionizing radiation (radiotherapy) at the core of paediatric cancer therapies, its direct and indirect effects can have lifelong negative impacts on paediatric growth and maintenance of skeletal muscle. Utilizing our recently developed preclinical rhabdomyosarcoma mouse model, we investigated the late effects of paediatric radiation treatment on skeletal muscles from late adolescent (8 weeks old) and middle-aged (16 months old) mice. METHODS: Paediatric C57BL/6J male mice (3 weeks old) were injected with rhabdomyosarcoma cells into their right hindlimbs, and then fractionated irradiation (3 × 8.2 Gy) was administered to those limbs at 4 weeks old to eliminate the tumours. Radiation-alone and tumour-irradiated mice were assessed at either 8 weeks (3 weeks post-irradiation) or 16 months (14 months post-irradiation) of age for muscle physiology, myofibre characteristics, cell loss, histopathology, fibrosis, inflammatory gene expression, and fibrotic gene expression. RESULTS: Mice that received only paediatric radiation demonstrated reduced muscle mass (-17%, P < 0.001), muscle physiological function (-25%, P < 0.01), muscle contractile kinetics (-25%, P < 0.05), satellite cell number (-45%, P < 0.05), myofibre cross-sectional area (-30%, P < 0.0001), and myonuclear number (-17%, P < 0.001). Paediatric radiation increased inflammatory gene expression, increased fibrotic gene expression, and induced extracellular matrix protein deposition (fibrosis) with tumour elimination exacerbating some phenotypes. Paediatric tumour-eliminated mice demonstrated exacerbated deficits to function (-20%, P < 0.05) and myofibre size (-17%, P < 0.001) in some muscles as well as further increases to inflammatory and fibrotic gene expression. Examining the age-related effects of paediatric radiotherapy in middle-aged mice, we found persistent myofibre atrophy (-20%, P < 0.01), myonuclear loss (-18%, P < 0.001), up-regulated inflammatory and fibrotic signalling, and lifelong fibrosis. CONCLUSIONS: The results from this paediatric radiotherapy model are consistent and recapitulate the clinical and molecular features of accelerated sarcopenia, musculoskeletal frailty, and radiation-induced fibrosis experienced by paediatric cancer survivors. We believe that this preclinical mouse model is well poised for future mechanistic insights and therapeutic interventions that improve the quality of life for paediatric cancer survivors.

STonKGs: a sophisticated transformer trained on biomedical text and knowledge graphs.

MOTIVATION: The majority of biomedical knowledge is stored in structured databases or as unstructured text in scientific publications. This vast amount of information has led to numerous machine learning-based biological applications using either text through natural language processing (NLP) or structured data through knowledge graph embedding models. However, representations based on a single modality are inherently limited. RESULTS: To generate better representations of biological knowledge, we propose STonKGs, a Sophisticated Transformer trained on biomedical text and Knowledge Graphs (KGs). This multimodal Transformer uses combined input sequences of structured information from KGs and unstructured text data from biomedical literature to learn joint representations in a shared embedding space. First, we pre-trained STonKGs on a knowledge base assembled by the Integrated Network and Dynamical Reasoning Assembler consisting of millions of text-triple pairs extracted from biomedical literature by multiple NLP systems. Then, we benchmarked STonKGs against three baseline models trained on either one of the modalities (i.e. text or KG) across eight different classification tasks, each corresponding to a different biological application. Our results demonstrate that STonKGs outperforms both baselines, especially on the more challenging tasks with respect to the number of classes, improving upon the F1-score of the best baseline by up to 0.084 (i.e. from 0.881 to 0.965). Finally, our pre-trained model as well as the model architecture can be adapted to various other transfer learning applications. AVAILABILITY AND IMPLEMENTATION: We make the source code and the Python package of STonKGs available at GitHub (https://github.com/stonkgs/stonkgs) and PyPI (https://pypi.org/project/stonkgs/). The pre-trained STonKGs models and the task-specific classification models are respectively available at https://huggingface.co/stonkgs/stonkgs-150k and https://zenodo.org/communities/stonkgs. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Insights into muscle stem cell dynamics during postnatal development.

During development, resident stem cell populations contribute to the growth and maturation of tissue and organs. In skeletal muscle, muscle stem cells, or satellite cells (SCs), are responsible for the maturation of postnatal myofibers. However, the role SCs play in later stages of postnatal growth, and thus, when they enter a mature quiescent state is controversial. Here, we discuss the current literature regarding the role SCs play in all stages of postnatal growth, from birth to puberty onset to young adulthood. We additionally highlight the implications of SC loss or dysfunction during developmental stages, both in the context of experimental paradigms and disease settings.

Author-sourced capture of pathway knowledge in computable form using Biofactoid.

Making the knowledge contained in scientific papers machine-readable and formally computable would allow researchers to take full advantage of this information by enabling integration with other knowledge sources to support data analysis and interpretation. Here we describe Biofactoid, a web-based platform that allows scientists to specify networks of interactions between genes, their products, and chemical compounds, and then translates this information into a representation suitable for computational analysis, search and discovery. We also report the results of a pilot study to encourage the wide adoption of Biofactoid by the scientific community.

Increased myocellular lipid and IGFBP-3 expression in a pre-clinical model of pancreatic cancer-related skeletal muscle wasting.

BACKGROUND: Skeletal muscle wasting (SMW) in cancer patients is associated with increased morbidity, mortality, treatment intolerance and discontinuation, and poor quality of life. This is particularly true for patients with pancreatic ductal adenocarcinoma (PDAC), as over 85% experience SMW, which is responsible for ~30% of patient deaths. While the established paradigm to explain SMW posits that muscle catabolism from systemic inflammation and nutritional deficiencies, the cause of death, and the cellular and molecular mechanisms responsible remain to be elucidated. To address this, we investigated the relationship between tumour burden and survival in the KCKO murine PDAC model. METHODS: Female C57BL/6J mice 6-8 weeks of age underwent orthotopic injection with KCKO-luc tumour cells. Solid tumour was verified on Day 5, post-tumour inoculation. In vivo, longitudinal lean mass and tumour burden were assessed via dual-energy X-ray absorptiometry and IVIS imaging, respectively, and total body weight was assessed, weekly. Animals were sacrificed at a designated end point of 'failure to thrive'. After sacrifice, lower limb hind muscles were harvested for histology and RNA extraction. RESULTS: We found a strong correlation between primary tumour size and survival (r2  = 0.83, P < 0.0001). A significant decrease in lower limb lean mass was first detected at Day 38 post-implantation vs. no tumour controls (NTCs) (P < 0.0001). SMW was confirmed by histology, which demonstrated a 38%, 32.7%, and 39.9% decrease in fibre size of extensor digitorum longus, soleus, and tibialis anterior muscles, respectively, in PDAC mice vs. NTC (P < 0.002). Histology also revealed a 67.6% increase in haematopoietic cells within the muscle of PDAC mice when compared with NTC. Bulk RNAseq on muscles from PDAC mice vs. NTC revealed significant increases in c/ebpß/Δ, il-1, il-6, and tnf gene expression. Pathway analyses to identify potential upstream factors revealed increased adipogenic gene expression, including a four-fold increase in igfbp-3. Histomorphometry of Oil Red-O staining for fat content in tibialis anterior muscles demonstrated a 95.5% increase in positively stained fibres from PDAC mice vs. NTC. CONCLUSIONS: Together, these findings support a novel model of PDAC-associated SMW and mortality in which systemic inflammation leads to inflammatory cell infiltration into skeletal muscle with up-regulated myocellular lipids.

GeneWalk identifies relevant gene functions for a biological context using network representation learning.

A bottleneck in high-throughput functional genomics experiments is identifying the most important genes and their relevant functions from a list of gene hits. Gene Ontology (GO) enrichment methods provide insight at the gene set level. Here, we introduce GeneWalk ( github.com/churchmanlab/genewalk ) that identifies individual genes and their relevant functions critical for the experimental setting under examination. After the automatic assembly of an experiment-specific gene regulatory network, GeneWalk uses representation learning to quantify the similarity between vector representations of each gene and its GO annotations, yielding annotation significance scores that reflect the experimental context. By performing gene- and condition-specific functional analysis, GeneWalk converts a list of genes into data-driven hypotheses.

shinyDepMap, a tool to identify targetable cancer genes and their functional connections from Cancer Dependency Map data.

Individual cancers rely on distinct essential genes for their survival. The Cancer Dependency Map (DepMap) is an ongoing project to uncover these gene dependencies in hundreds of cancer cell lines. To make this drug discovery resource more accessible to the scientific community, we built an easy-to-use browser, shinyDepMap (https://labsyspharm.shinyapps.io/depmap). shinyDepMap combines CRISPR and shRNA data to determine, for each gene, the growth reduction caused by knockout/knockdown and the selectivity of this effect across cell lines. The tool also clusters genes with similar dependencies, revealing functional relationships. shinyDepMap can be used to (1) predict the efficacy and selectivity of drugs targeting particular genes; (2) identify maximally sensitive cell lines for testing a drug; (3) target hop, that is, navigate from an undruggable protein with the desired selectivity profile, such as an activated oncogene, to more druggable targets with a similar profile; and (4) identify novel pathways driving cancer cell growth and survival.

Radiation-Induced Damage to Prepubertal Pax7+ Skeletal Muscle Stem Cells Drives Lifelong Deficits in Myofiber Size and Nuclear Number.

During prepubertal development, muscle stem cells (satellite cells, SCs) actively contribute to myofiber growth. Because some SCs are active during this time, they may be particularly susceptible to damage. Using a Small Animal Radiation Research Platform (SARRP), we investigated the effects of local fractionated radiation treatment on prepubertal SCs. Immediately after this regimen, there was a reduction in SC number. Although surviving SCs had deficiencies in function, some myogenic potential remained. Indeed, some muscle regenerative capacity persisted immediately after irradiation. Lastly, we assessed the long-term consequences of radiation-induced SC loss during prepuberty. We observed a reduction of myofiber size and corresponding loss of nuclei in both fast- and slow-contracting muscles 14 months post-irradiation. Notably, prepubertal SC depletion mimicked these lifelong deficits. This work highlights the susceptibility of prepubertal SCs to radiation exposure. We also reveal the importance of prepubertal SC contribution to the lifelong maintenance of skeletal muscle.

Chemoradiation impairs myofiber hypertrophic growth in a pediatric tumor model.

Pediatric cancer treatment often involves chemotherapy and radiation, where off-target effects can include skeletal muscle decline. The effect of such treatments on juvenile skeletal muscle growth has yet to be investigated. We employed a small animal irradiator to administer fractionated hindlimb irradiation to juvenile mice bearing implanted rhabdomyosarcoma (RMS) tumors. Hindlimb-targeted irradiation (3 × 8.2 Gy) of 4-week-old mice successfully eliminated RMS tumors implanted one week prior. After establishment of this preclinical model, a cohort of tumor-bearing mice were injected with the chemotherapeutic drug, vincristine, alone or in combination with fractionated irradiation (5 × 4.8 Gy). Single myofiber analysis of fast-contracting extensor digitorum longus (EDL) and slow-contracting soleus (SOL) muscles was conducted 3 weeks post-treatment. Although a reduction in myofiber size was apparent, EDL and SOL myonuclear number were differentially affected by juvenile irradiation and/or vincristine treatment. In contrast, a decrease in myonuclear domain (myofiber volume/myonucleus) was observed regardless of muscle or treatment. Thus, inhibition of myofiber hypertrophic growth is a consistent feature of pediatric cancer treatment.

Inhibition of inflammatory CCR2 signaling promotes aged muscle regeneration and strength recovery after injury.

Muscle regeneration depends on a robust albeit transient inflammatory response. Persistent inflammation is a feature of age-related regenerative deficits, yet the underlying mechanisms are poorly understood. Here, we find inflammatory-related CC-chemokine-receptor 2 (Ccr2) expression in non-hematopoietic myogenic progenitors (MPs) during regeneration. After injury, the expression of Ccr2 in MPs corresponds to the levels of its ligands, the chemokines Ccl2, 7, and 8. We find stimulation of Ccr2-activity inhibits MP fusion and contribution to myofibers. This occurs in association with increases in MAPKp38δ/γ signaling, MyoD phosphorylation, and repression of the terminal myogenic commitment factor Myogenin. High levels of Ccr2-chemokines are a feature of regenerating aged muscle. Correspondingly, deletion of Ccr2 in MPs is necessary for proper fusion into regenerating aged muscle. Finally, opportune Ccr2 inhibition after injury enhances aged regeneration and functional recovery. These results demonstrate that inflammatory-induced activation of Ccr2 signaling in myogenic cells contributes to aged muscle regenerative decline.

Production of a NiO/Al primary battery employing powder-based electrodes.

This paper describes the use of aluminum and zinc as anodic materials for a battery employing nickel (II) oxide (NiO) as cathode. Comparison of both materials resulted in the development of a compact, cost effective, and easy to use primary NiO/Al battery employing an alkaline electrolyte. The system features electrodes composed of powder forms of the active materials on modified paper substrates that are contained in a simple multilayer design utilizing thin laminated plastic materials to provide structure and flexibility to the battery as well as a paper separator. Various concentrations of potassium hydroxide (KOH) electrolyte were examined and maximum performance was observed at 6 M KOH. A maximum current density and power density of 1.94 mA/cm2 and 1 mW/cm2 , respectively was achieved. This user-friendly device was able to produce a maximum capacity of 2.33 mAh/g when 2 mA/g was applied. This work demonstrates the viability of a paper-based battery featuring powder electrodes as a possible power source for microelectronic devices.

Synthetic Lethal Interaction of SHOC2 Depletion with MEK Inhibition in RAS-Driven Cancers.

The mitogen-activated protein kinase (MAPK) pathway is a critical effector of oncogenic RAS signaling, and MAPK pathway inhibition may be an effective combination treatment strategy. We performed genome-scale loss-of-function CRISPR-Cas9 screens in the presence of a MEK1/2 inhibitor (MEKi) in KRAS-mutant pancreatic and lung cancer cell lines and identified genes that cooperate with MEK inhibition. While we observed heterogeneity in genetic modifiers of MEKi sensitivity across cell lines, several recurrent classes of synthetic lethal vulnerabilities emerged at the pathway level. Multiple members of receptor tyrosine kinase (RTK)-RAS-MAPK pathways scored as sensitizers to MEKi. In particular, we demonstrate that knockout, suppression, or degradation of SHOC2, a positive regulator of MAPK signaling, specifically cooperated with MEK inhibition to impair proliferation in RAS-driven cancer cells. The depletion of SHOC2 disrupted survival pathways triggered by feedback RTK signaling in response to MEK inhibition. Thus, these findings nominate SHOC2 as a potential target for combination therapy.

Re-curation and rational enrichment of knowledge graphs in Biological Expression Language.

The rapid accumulation of new biomedical literature not only causes curated knowledge graphs (KGs) to become outdated and incomplete, but also makes manual curation an impractical and unsustainable solution. Automated or semi-automated workflows are necessary to assist in prioritizing and curating the literature to update and enrich KGs. We have developed two workflows: one for re-curating a given KG to assure its syntactic and semantic quality and another for rationally enriching it by manually revising automatically extracted relations for nodes with low information density. We applied these workflows to the KGs encoded in Biological Expression Language from the NeuroMMSig database using content that was pre-extracted from MEDLINE abstracts and PubMed Central full-text articles using text mining output integrated by INDRA. We have made this workflow freely available at https://github.com/bel-enrichment/bel-enrichment.