Fourier-Transform Infrared Spectroscopy of Skeletal Muscle Tissue: Expanding Biomarkers in Primary Mitochondrial Myopathies

Mitochondrial Biomarkers in the Omics Era: A Clinical-Pathophysiological Perspective

Mitochondrial diseases (MDs) affect 4300 individuals, with different ages of presentation and manifestation in any organ. How defects in mitochondria can cause such a diverse range of human diseases remains poorly understood. In recent years, several published research articles regarding the metabolic and protein profiles of these neurogenetic disorders have helped shed light on the pathogenetic mechanisms. By investigating different pathways in MDs, often with the aim of identifying disease biomarkers, it is possible to identify molecular processes underlying the disease. In this perspective, omics technologies such as proteomics and metabolomics considered in this review, can support unresolved mitochondrial questions, helping to improve outcomes for patients.

A clinical approach to diagnosis and management of mitochondrial myopathies

This paper provides an overview of the different types of mitochondrial myopathies (MM), associated phenotypes, genotypes as well as a practical clinical approach towards disease diagnosis, surveillance, and management. nDNA-related MM are more common in pediatric-onset disease whilst mtDNA-related MMs are more frequent in adults. Genotype-phenotype correlation in MM is challenging due to clinical and genetic heterogeneity. The multisystemic nature of many MMs adds to the diagnostic challenge. Diagnostic approaches utilizing genetic sequencing with next generation sequencing approaches such as gene panel, exome and genome sequencing are available. This aids molecular diagnosis, heteroplasmy detection in MM patients and furthers knowledge of known mitochondrial genes. Precise disease diagnosis can end the diagnostic odyssey for patients, avoid unnecessary testing, provide prognosis, facilitate anticipatory management, and enable access to available therapies or clinical trials. Adjunctive tests such as functional and exercise testing could aid surveillance of MM patients. Management requires a multi-disciplinary approach, systemic screening for comorbidities, cofactor supplementation, avoidance of substances that inhibit the respiratory chain and exercise training. This update of the current understanding on MMs provides practical perspectives on current diagnostic and management approaches for this complex group of disorders.

Exploration of macromolecular phenotype of human skeletal muscle in diabetes using infrared spectroscopy

Introduction

The global burden of diabetes mellitus is escalating, and more efficient investigative strategies are needed for a deeper understanding of underlying pathophysiological mechanisms. The crucial role of skeletal muscle in carbohydrate and lipid metabolism makes it one of the most susceptible tissues to diabetes-related metabolic disorders. In tissue studies, conventional histochemical methods have several technical limitations and have been shown to inadequately characterise the biomolecular phenotype of skeletal muscle to provide a holistic view of the pathologically altered proportions of macromolecular constituents.

Materials and methods

In this pilot study, we examined the composition of five different human skeletal muscles from male donors diagnosed with type 2 diabetes and non-diabetic controls. We analysed the lipid, glycogen, and collagen content in the muscles in a traditional manner with histochemical assays using different staining techniques. This served as a reference for comparison with the unconventional analysis of tissue composition using Fourier-transform infrared spectroscopy as an alternative methodological approach.

Results

A thorough chemometric post-processing of the infrared spectra using a multi-stage spectral decomposition allowed the simultaneous identification of various compositional details from a vibrational spectrum measured in a single experiment. We obtained multifaceted information about the proportions of the different macromolecular constituents of skeletal muscle, which even allowed us to distinguish protein constituents with different structural properties. The most important methodological steps for a comprehensive insight into muscle composition have thus been set and parameters identified that can be used for the comparison between healthy and diabetic muscles.

Conclusion

We have established a methodological framework based on vibrational spectroscopy for the detailed macromolecular analysis of human skeletal muscle that can effectively complement or may even serve as an alternative to histochemical assays. As this is a pilot study with relatively small sample sets, we remain cautious at this stage in drawing definitive conclusions about diabetes-related changes in skeletal muscle composition. However, the main focus and contribution of our work has been to provide an alternative, simple and efficient approach for this purpose. We are confident that we have achieved this goal and have brought our methodology to a level from which it can be successfully transferred to a large-scale study that allows the effects of diabetes on skeletal muscle composition and the interrelationships between the macromolecular tissue alterations due to diabetes to be investigated.

Biomarkers: Promising and valuable tools towards diagnosis, prognosis and treatment of Covid-19 and other diseases

The use of biomarkers as early warning systems in the evaluation of disease risk has increased markedly in the last decade. Biomarkers are indicators of typical biological processes, pathogenic processes, or pharmacological reactions to therapy. The application and identification of biomarkers in the medical and clinical fields have an enormous impact on society. In this review, we discuss the history, various definitions, classifications, characteristics, and discovery of biomarkers. Furthermore, the potential application of biomarkers in the diagnosis, prognosis, and treatment of various diseases over the last decade are reviewed. The present review aims to inspire readers to explore new avenues in biomarker research and development.

Fast identification of off-target liabilities in early antibiotic discovery with Fourier-transform infrared spectroscopy

Structural modifications of known antibiotic scaffolds have kept the upper hand on resistance, but we are on the verge of not having antibiotics for many common infections. Mechanism-based discovery assays reveal novelty, exclude off-target liabilities, and guide lead optimization. For that, we developed a fast and automatable protocol using high-throughput Fourier-transform infrared spectroscopy (FTIRS). Metabolic fingerprints of Staphylococcus aureus and Escherichia coli exposed to 35 compounds, dissolved in dimethyl sulfoxide (DMSO) or water, were acquired. Our data analysis pipeline identified biomarkers of off-target effects, optimized spectral preprocessing, and identified the top-performing machine learning algorithms for off-target liabilities and mechanism of action (MOA) identification. Spectral bands with known biochemical associations more often yielded more significant biomarkers of off-target liabilities when bacteria were exposed to compounds dissolved in water than DMSO. Highly discriminative models distinguished compounds with predominant off-target effects from antibiotics with well-defined MOA (AUROC > 0.87, AUPR > 0.79, F1 > 0.81), and from the latter predicted their MOA (AUROC > 0.88, AUPR > 0.70, F1 > 0.70). The compound solvent did not affect predictive models. FTIRS is fast, simple, inexpensive, automatable, and highly effective at predicting MOA and off-target liabilities. As such, FTIRS mechanism-based screening assays can be applied for hit discovery and to guide lead optimization during the early stages of antibiotic discovery.