In Vivo Fiber Optic Raman Spectroscopy of Muscle in Preclinical Models of Amyotrophic Lateral Sclerosis and Duchenne Muscular Dystrophy

Conformational fingerprinting with Raman spectroscopy reveals protein structure as a translational biomarker of muscle pathology

Neuromuscular disorders are a group of conditions that can result in weakness of skeletal muscles. Examples include fatal diseases such as amyotrophic lateral sclerosis and conditions associated with high morbidity such as myopathies (muscle diseases). Many of these disorders are known to have abnormal protein folding and protein aggregates. Thus, easy to apply methods for the detection of such changes may prove useful diagnostic biomarkers. Raman spectroscopy has shown early promise in the detection of muscle pathology in neuromuscular disorders and is well suited to characterising the conformational profiles relating to protein secondary structure. In this work, we assess if Raman spectroscopy can detect differences in protein structure in muscle in the setting of neuromuscular disease. We utilise in vivo Raman spectroscopy measurements from preclinical models of amyotrophic lateral sclerosis and the myopathy Duchenne muscular dystrophy, together with ex vivo measurements of human muscle samples from individuals with and without myopathy. Using quantitative conformation profiling and matrix factorisation we demonstrate that quantitative 'conformational fingerprinting' can be used to identify changes in protein folding in muscle. Notably, myopathic conditions in both preclinical models and human samples manifested a significant reduction in α-helix structures, with concomitant increases in β-sheet and, to a lesser extent, nonregular configurations. Spectral patterns derived through non-negative matrix factorisation were able to identify myopathy with a high accuracy (79% in mouse, 78% in human tissue). This work demonstrates the potential of conformational fingerprinting as an interpretable biomarker for neuromuscular disorders.

Combining electromyography and Raman spectroscopy: optical EMG

INTRODUCTION/AIMS

Electromyography (EMG) remains a key component of the diagnostic work-up for suspected neuromuscular disease, but it does not provide insight into the molecular composition of muscle which can provide diagnostic information. Raman spectroscopy is an emerging neuromuscular biomarker capable of generating highly specific, molecular fingerprints of tissue. Here, we present "optical EMG," a combination of EMG and Raman spectroscopy, achieved using a single needle.

METHODS

An optical EMG needle was created to collect electrophysiological and Raman spectroscopic data during a single insertion. We tested functionality with in vivo recordings in the SOD1G93A mouse model of amyotrophic lateral sclerosis (ALS), using both transgenic (n = 10) and non-transgenic (NTg, n = 7) mice. Under anesthesia, compound muscle action potentials (CMAPs), spontaneous EMG activity and Raman spectra were recorded from both gastrocnemius muscles with the optical EMG needle. Standard concentric EMG needle recordings were also undertaken. Electrophysiological data were analyzed with standard univariate statistics, Raman data with both univariate and multivariate analyses.

RESULTS

A significant difference in CMAP amplitude was observed between SOD1G93A and NTg mice with optical EMG and standard concentric needles (p = .015 and p = .011, respectively). Spontaneous EMG activity (positive sharp waves) was detected in transgenic SOD1G93A mice only. Raman spectra demonstrated peaks associated with key muscle components. Significant differences in molecular composition between SOD1G93A and NTg muscle were identified through the Raman spectra.

DISCUSSION

Optical EMG can provide standard electrophysiological data and molecular Raman data during a single needle insertion and represents a potential biomarker for neuromuscular disease.

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.

Development of a micro-Raman system for in vivo studying the mechanism of laser biological effects

The laser irradiation on organism will produce a series of biological effects, which can be used for basic medical research, diagnosis and treatments of diseases. However, the mechanism of this biological effects is still unclear. As a sensitive molecular monitoring technique, Raman spectroscopy has became a very popular detection method in biomedical research especially in vivo study. In this paper, we present a compact and flexible micro-Raman system for in vivo studying the mechanism of laser biological effects. The system has the two functions of laser induction and Raman measurement, which can realize the micro-area radiation of laser and simultaneously collect the corresponding Raman spectra in vivo. The detection method provided by this home-built system is able to deepen the understanding of laser biological effects mechanism at molecular level, so it is expected that the system is significant for the treatments and diagnosis of diseases in the near future.

Laser tweezers Raman spectroscopy combined with machine learning for diagnosis of Alzheimer's disease

Alzheimer's disease (AD) is a common nervous system disease to affect mostly elderly people over the age of 65 years. However, the diagnosis of AD is mainly depend on the imaging examination, clinical assessments and neuropsychological tests, which may get error diagnosis results and are not able to detect early AD. Here, a rapid, non-invasive, and high accuracy diagnostic method for AD especially early AD is provided based on the laser tweezers Raman spectroscopy (LTRS) combined with machine learning algorithms. AD platelets from different 3xTg-AD transgenic rats at different stages of disease are captured to collect high signal-to-noise ratio Raman signals without contact by LTRS, which is then combined with partial least squares discriminant analysis (PLS-DA), support vector machine (SVM) and principal component analysis (PCA)-canonical discriminate function (CDA) for classification. The results show that the normal and diseased platelets at 3-, 6- and 12-month AD are successfully distinguished and the accuracy is 91%, 68% and 97% respectively, which demonstrates the suggested method can provide a precise detection for AD diagnosis at early, middle and advanced stages.

In vivo spectroscopy: optical fiber probes for clinical applications

INTRODUCTION

Fiber optic probe based in-vivo spectroscopy techniques are fast and highly objective methods for intraoperative diagnoses and minimally invasive surgical interventions for all procedures where endoscopic observations are carried out for cancers of different types. The Raman spectral features provide molecular fingerprint-type information and can reveal the subjects' pathological state in label-free manner, making endoscopy multiplexed fiber optic probe-based devices with the potential for translation from bench to bedside for routine applications.

AREAS COVERED

This review provides a general overview of different fiber-optic probes for in-vivo measurements with emphasis on Raman spectroscopy for biomedical application. Various aspects such as fiber-optic probe, radiation source, detector, and spectrometer for extracting optimum spectral features have also been discussed.

EXPERT OPINION

: Optical spectroscopy-based fiber probe systems with "Chip-on-Tip" technology, combined with machine learning, can in the near future, become a complimentary diagnostic tool to magnetic resonance imaging (MRI), computed tomography (CT) scan, ultrasound, etc. Hyperspectral imaging and fluorescence-based devices are in the advanced stage of technology readiness level (TRL), and with advances in lasers and miniature spectroscopy systems, probe-based Raman devices are also coming up.

Fibre optic Raman spectroscopy for the evaluation of disease state in Duchenne muscular dystrophy: an assessment using the mdx model and human muscle

Introduction/Aims

Raman spectroscopy is an emerging technique for the evaluation of muscle disease. In this study we evaluate the ability of in vivo intramuscular Raman spectroscopy to detect the effects of voluntary running in the mdx model of Duchenne muscular dystrophy (DMD). We also compare mdx data with muscle spectra from human DMD patients.

Methods

Thirty 90‐day‐old mdx mice were randomly allocated to an exercised group (48‐hour access to a running wheel) and an unexercised group (n = 15 per group). In vivo Raman spectra were collected from both gastrocnemius muscles and histopathological assessment subsequently performed. Raman data were analyzed using principal component analysis–fed linear discriminant analysis (PCA‐LDA). Exercised and unexercised mdx muscle spectra were compared with human DMD samples using cosine similarity.

Results

Exercised mice ran an average of 6.5 km over 48 hours, which induced a significant increase in muscle necrosis (P = .03). PCA‐LDA scores were significantly different between the exercised and unexercised groups (P < .0001) and correlated significantly with distance run (P = .01). Raman spectra from exercised mice more closely resembled human spectra than those from unexercised mice.

Discussion

Raman spectroscopy provides a readout of the biochemical alterations in muscle in both the mdx mouse and human DMD muscle.

Multi-Omics Analysis of the Microbiome and Metabolome Reveals the Relationship Between the Gut Microbiota and Wooden Breast Myopathy in Broilers

Wooden breast (WB) is a widely prevalent myopathy in broiler chickens. However, the role of the gut microbiota in this myopathy remains largely unknown, in particular the regulatory effect of gut microbiota in the modulation of muscle metabolism. Totally, 300 1-day-old Arbor Acres broilers were raised until 49 days and euthanized, and the breast filets were classified as normal (NORM), mild (MILD), or severe wooden breast (SEV). Birds with WB comprised 27.02% of the individuals. Severe WB filets had a greater L* value, a* value, and dripping loss but a lower pH (P < 0.05). WB filets had abundant myofiber fragmentation, with a lower average myofiber caliber and more fibers with a diameter of <20 μm (P < 0.05). The diversity of the intestinal microflora was decreased in birds with severe WB, with decreases in Chao 1, and observed species indices. At the phylum level, birds with severe WB had a lower Firmicutes/Bacteroidetes ratio (P = 0.098) and a decreased abundance of Verrucomicrobia (P < 0.05). At the species level, gut microbiota were positively correlated with 131 digesta metabolites in pathways of glutamine and glutamate metabolism and arginine biosynthesis but were negatively correlated with 30 metabolites in the pathway of tyrosine metabolism. In plasma, WB induced five differentially expressed metabolites (DEMs), including anserine and choline, which were related to the severity of the WB lesion. The microbial-derived metabolites, including guanidoacetic acid, antiarol, and (2E)-decenoyl-ACP, which entered into plasma were related to meat quality traits and myofiber traits. In summary, WB filets differed in gut microbiota, digesta, and plasma metabolites. Gut microbiota respond to the wooden breast myopathy by driving dynamic changes in digesta metabolites that eventually enter the plasma.

Rapid identification of human muscle disease with fibre optic Raman spectroscopy

We demonstrate the use of fibre optic Raman spectroscopy for the rapid identification of muscle disorders.