Potential of FTIR Spectroscopy Applied to Exosomes for Alzheimer's Disease Discrimination: A Pilot Study

Phosphoproteome Microarray Analysis of Extracellular Particles as a Tool to Explore Novel Biomarker Candidates for Alzheimer's Disease

Phosphorylation plays a key role in Alzheimer's disease (AD) pathogenesis, impacting distinct processes such as amyloid-beta (Aβ) peptide production and tau phosphorylation. Impaired phosphorylation events contribute to senile plaques and neurofibrillary tangles' formation, two major histopathological hallmarks of AD. Blood-derived extracellular particles (bdEP) can represent a disease-related source of phosphobiomarker candidates, and hence, in this pilot study, bdEP of Control and AD cases were analyzed by a targeted phosphoproteomics approach using a high-density microarray that featured at least 1145 pan-specific and 913 phosphosite-specific antibodies. This approach, innovatively applied to bdEP, allowed the identification of 150 proteins whose expression levels and/or phosphorylation patterns were significantly altered across AD cases. Gene Ontology enrichment and Reactome pathway analysis unraveled potentially relevant molecular targets and disease-associated pathways, and protein-protein interaction networks were constructed to highlight key targets. The discriminatory value of both the total proteome and the phosphoproteome was evaluated by univariate and multivariate approaches. This pilot experiment supports that bdEP are enriched in phosphotargets relevant in an AD context, holding value as peripheral biomarker candidates for disease diagnosis.

Advancements in Mid-Infrared spectroscopy of extracellular vesicles

Extracellular vesicles (EVs) are lipid vesicles secreted by all cells into the extracellular space and act as nanosized biological messengers among cells. They carry a specific molecular cargo, composed of lipids, proteins, nucleic acids, and carbohydrates, which reflects the state of their parent cells. Due to their remarkable structural and compositional heterogeneity, characterizing EVs, particularly from a biochemical perspective, presents complex challenges. In this context, mid-infrared (IR) spectroscopy is emerging as a valuable tool, providing researchers with a comprehensive and label-free spectral fingerprint of EVs in terms of their specific molecular content. This review aims to provide an up-to-date critical overview of the major advancements in mid-IR spectroscopy of extracellular vesicles, encompassing both fundamental and applied research achievements. We also systematically emphasize the new possibilities offered by the integration of emerging cutting-edge IR technologies, such as tip-enhanced and surface-enhanced spectroscopy approaches, along with the growing use of machine learning for data analysis and spectral interpretation. Additionally, to assist researchers in navigating this intricate subject, our manuscript includes a wide and detailed collection of the spectral peaks that have been assigned to EV molecular constituents up to now in the literature.

FTIR Spectroscopy and Blood-Derived Extracellular Vesicles Duo in Alzheimer's Disease

Background

Alzheimer's disease (AD) diagnosis is difficult, and new accurate tools based on peripheral biofluids are urgently needed. Extracellular vesicles (EVs) emerged as a valuable source of biomarker profiles for AD, since their cargo is disease-specific and these can be easily isolated from easily accessible biofluids, as blood. Fourier Transform Infrared (FTIR) spectroscopy can be employed to analyze EVs and obtain the spectroscopic profiles from different regions of the spectra, simultaneously characterizing carbohydrates, nucleic acids, proteins, and lipids.

Objective

The aim of this study was to identify blood-derived EVs (bdEVs) spectroscopic signatures with AD discriminatory potential.

Methods

Herein, FTIR spectra of bdEVs from two biofluids (serum and plasma) and distinct sets of Controls and AD cases were acquired, and EVs' spectra analyzed.

Results

Analysis of bdEVs second derivative peaks area revealed differences between Controls and AD cases in distinct spectra regions, assigned to carbohydrates and nucleic acids, amides, and lipids.

Conclusions

EVs' spectroscopic profiles presented AD discriminatory value, supporting the use of bdEVs combined with FTIR as a screening or complementary tool for AD diagnosis.

Mesenchymal stem cells-derived exosomes: novel carriers for nanoparticle to combat cancer

BACKGROUND

The advancement in novel cancer therapeutics brought a platform combining the properties of exosomes with nanoparticles to precision medicine. The novel therapeutic approach aim is cancer-targeted therapy. Exosomes from mesenchymal stem cells (MSCs-Exo) exhibit unique properties in cancer therapies, which makes them an ideal tool for delivering therapeutic agents into tumor cells. The key role of natural MSCs-Exo is controversial in cancer therapy; however, they can be engineered at their surface or cargo to serve as a smart drug delivery system for cancer-targeted therapy. In the last few years, researchers harnessed nanotechnology to enforce MSCs-Exo for cancer management including, tumor cell tracking, imaging, and tumor cell killing. Different nanoparticles such as gold nanoparticles have particularly been incorporated into MSCs-Exo, which showed an efficient accumulation at the site of tumor with improved anticancer impact. These findings indicate that a hybrid of exosomes-nanoparticles may serve as combination therapy for the effective removal of cancers.

SHORT CONCLUSION

Although exhibiting impressive potential, the use of nanoparticle-loaded MSCs-Exo as a drug-delivery tool has been troubled by some challenges, therefore, translation to clinic prerequisites further scrutiny. In this review, we focus on nanoparticle-loaded MSCs-Exo as a new cancer therapy and discuss engineered MSC-Exo for target therapy.

Targeted Metabolomic Analysis of the Eye Tissue of Triple Transgenic Alzheimer's Disease Mice at an Early Pathological Stage

Alzheimer's disease (AD) is a severe neurodegenerative disease in older people. Despite some consensus on pathogenesis of AD established by previous researches, further elucidation is still required for better understanding. This study analyzed the eye tissues of 2- and 6-month-old triple transgenic AD (3 × Tg-AD) male mice and age-sex-matched wild-type (WT) mice using a targeted metabolomics approach. Compared with WT mice, 20 and 44 differential metabolites were identified in 2- and 6-month-old AD mice, respectively. They were associated with purine metabolism, pantothenate and CoA biosynthesis, pyruvate metabolism, lysine degradation, glycolysis/gluconeogenesis, and pyrimidine metabolism pathways. Among them, 8 metabolites presented differences in both the two groups, and 5 of them showed constant trend of change. The results indicated that the eye tissues of 3 × Tg-AD mice underwent changes in the early stages of the disease, with changes in metabolites observed at 2 months of age and more pronounced at 6 months of age, which is consistent with our previous studies on hippocampal targeted metabolomics in 3 × Tg-AD mice. Therefore, a joint analysis of data from this study and previous hippocampal study was performed, and the differential metabolites and their associated mechanisms were similar in eye and hippocampal tissues, but with tissue specificity.

Antenna-enhanced mid-infrared detection of extracellular vesicles derived from human cancer cell cultures

BACKGROUND

Extracellular Vesicles (EVs) are sub-micrometer lipid-bound particles released by most cell types. They are considered a promising source of cancer biomarkers for liquid biopsy and personalized medicine due to their specific molecular cargo, which provides biochemical information on the state of parent cells. Despite this potential, EVs translation process in the diagnostic practice is still at its birth, and the development of novel medical devices for their detection and characterization is highly required.

RESULTS

In this study, we demonstrate mid-infrared plasmonic nanoantenna arrays designed to detect, in the liquid and dry phase, the specific vibrational absorption signal of EVs simultaneously with the unspecific refractive index sensing signal. For this purpose, EVs are immobilized on the gold nanoantenna surface by immunocapture, allowing us to select specific EV sub-populations and get rid of contaminants. A wet sample-handling technique relying on hydrophobicity contrast enables effortless reflectance measurements with a Fourier-transform infrared (FTIR) spectro-microscope in the wavelength range between 10 and 3 µm. In a proof-of-principle experiment carried out on EVs released from human colorectal adenocarcinoma (CRC) cells, the protein absorption bands (amide-I and amide-II between 5.9 and 6.4 µm) increase sharply within minutes when the EV solution is introduced in the fluidic chamber, indicating sensitivity to the EV proteins. A refractive index sensing curve is simultaneously provided by our sensor in the form of the redshift of a sharp spectral edge at wavelengths around 5 µm, where no vibrational absorption of organic molecules takes place: this permits to extract of the dynamics of EV capture by antibodies from the overall molecular layer deposition dynamics, which is typically measured by commercial surface plasmon resonance sensors. Additionally, the described metasurface is exploited to compare the spectral response of EVs derived from cancer cells with increasing invasiveness and metastatic potential, suggesting that the average secondary structure content in EVs can be correlated with cell malignancy.

CONCLUSIONS

Thanks to the high protein sensitivity and the possibility to work with small sample volumes-two key features for ultrasensitive detection of extracellular vesicles- our lab-on-chip can positively impact the development of novel laboratory medicine methods for the molecular characterization of EVs.

Sustained release of sulforaphane by bioactive extracellular vesicles for neuroprotective effect on chick model

Novel studies have shown neurological treatment possibilities with extracellular vesicles (EVs) as natural particles with a special composition that are produced by different cell types. Their stability, natural structure, composition, and bioavailability make them good candidates as drug vehicles. Here, EVs were isolated from amniotic fluid (AF) through differential centrifugation, and characterized for size (<200 nm), structure, and composition, their effectiveness on the human PC12 cell line, and brain of chick embryos exposed to sodium valproate (animal autistic model). Sulforaphane (SFN) was employed as a bioactive compound and then encapsulated into Evs using three methods including passive (incubation), active (sonication), and active-passive (sonication-incubation). Further, the loading and in vitro releases of SFN fitted the Korsmeyer-Peppas (R²  = 0.99) kinetic model by non-Fickian diffusion case II (n = 0.44, passive loading) and Fickian diffusion case I (n = 0.41, active and active-passive loading). SFN-loaded EVs (SFN@EVs; 11 μM: 103 nM) stimulated hPC-12 cell proliferation. The gene expression analysis revealed that SFN@EVs could upregulate Nrf2 and reduce IL-6 expression. Eventually, histopathological results of the coronal cross-section of the chick embryos brain showed treatment with SFN@EVs. This treatment illustrated normality in the gray and white matter and the orientation of the bipolar neurons. Our findings showed EVs' potentially acting as a gene expression regulator in autism spectrum disorder.

Exosome Structures Supported by Machine Learning Can Be Used as a Promising Diagnostic Tool

Principal component analysis (PCA) as a machine-learning technique could serve in disease diagnosis and prognosis by evaluating the dynamic morphological features of exosomes via Cryo-TEM-imaging. This hypothesis was investigated after the crude isolation of similarly featured exosomes derived from the extracellular vehicles (EVs) of immature dendritic cells (IDCs) JAWSII. It is possible to identify functional molecular groups by FTIR, but the unique physical and morphological characteristics of exosomes can only be revealed by specialized imaging techniques such as cryo-TEM. On the other hand, PCA has the ability to examine the morphological features of each of these IDC-derived exosomes by considering software parameters such as various membrane projections and differences in Gaussians, Hessian, hue, and class to assess the 3D orientation, shape, size, and brightness of the isolated IDC-derived exosome structures. In addition, Brownian motions from nanoparticle tracking analysis of EV IDC-derived exosomes were also compared with EV IDC-derived exosome images collected by scanning electron microscopy and confocal microscopy. Sodium-Dodecyl-Sulphate-Polyacrylamide-Gel-Electrophoresis (SDS-PAGE) was performed to separate the protein content of the crude isolates showing that no considerable protein contamination occurred during the crude isolation technique of IDC-derived-exosomes. This is an important finding because no additional purification of these exosomes is required, making PCA analysis both valuable and novel.

Investigation of early biochemical alterations in myocardia of the diabetic db/db mice by FTIR microspectroscopy combined with machine learning

Diabetic cardiomyopathy (DbCM) is a serious complication of diabetes that affects about 12% of the diabetic population. Sensitive detection of diabetes-induced biochemical changes in the heart before symptoms appear can assist clinicians in developing targeted treatment plans and forensic pathologists in making accurate postmortem diagnoses. The Fourier transform infrared (FTIR) spectroscopy-based approach allows for the analysis of the sample biomolecular composition and variations. In the current study, the myocardial tissues of mouse models of type 2 diabetes mellitus (T2DM) at various ages (7, 12, and 21 weeks) were analyzed using FTIR microspectroscopy (FTIRM) in combination with machine learning algorithms. The carbonyl esters, olefinic=CH and CH₂ groups of lipids, total lipids, saccharides, and β-sheet to α-helix conformational transition in proteins increased significantly in diabetic mice myocardial tissues compared to healthy mice. Furthermore, partial least-squares discriminant analysis and random forest-guided partial least-squares discriminant analysis revealed the time-dependent progression of the spectral lipidomic profiles during the development of DbCM. Finally, a random forest classifier was developed for diagnosing DbCM, with 97.1% accuracy. This study demonstrates that FTIRM is a novel method for monitoring early biochemical changes in the myocardia of mice with T2DM.

Machine Learning-Assisted FTIR Analysis of Circulating Extracellular Vesicles for Cancer Liquid Biopsy

Extracellular vesicles (EVs) are abundantly released into the systemic circulation, where they show remarkable stability and harbor molecular constituents that provide biochemical information about their cells of origin. Due to this characteristic, EVs are attracting increasing attention as a source of circulating biomarkers for cancer liquid biopsy and personalized medicine. Despite this potential, none of the discovered biomarkers has entered the clinical practice so far, and novel approaches for the label-free characterization of EVs are highly demanded. In this regard, Fourier Transform Infrared Spectroscopy (FTIR) has great potential as it provides a quick, reproducible, and informative biomolecular fingerprint of EVs. In this pilot study, we investigated, for the first time in the literature, the capability of FTIR spectroscopy to distinguish between EVs extracted from sera of cancer patients and controls based on their mid-IR spectral response. For this purpose, EV-enriched suspensions were obtained from the serum of patients diagnosed with Hepatocellular Carcinoma (HCC) of nonviral origin and noncancer subjects. Our data point out the presence of statistically significant differences in the integrated intensities of major mid-IR absorption bands, including the carbohydrate and nucleic acids band, the protein amide I and II bands, and the lipid CH stretching band. Additionally, we used Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) for the automated classification of spectral data according to the shape of specific mid-IR spectral signatures. The diagnostic performances of the proposed spectral biomarkers, alone and combined, were evaluated using multivariate logistic regression followed by a Receiving Operator Curve analysis, obtaining large Areas Under the Curve (AUC = 0.91, 95% CI 0.81–1.0). Very interestingly, our analyses suggest that the discussed spectral biomarkers can outperform the classification ability of two widely used circulating HCC markers measured on the same groups of subjects, namely alpha-fetoprotein (AFP), and protein induced by the absence of vitamin K or antagonist-II (PIVKA-II).

Recent advances in optical label-free characterization of extracellular vesicles

Extracellular vesicles (EVs) are complex biological nanoparticles endogenously secreted by all eukaryotic cells. EVs carry a specific molecular cargo of proteins, lipids, and nucleic acids derived from cells of origin and play a significant role in the physiology and pathology of cells, organs, and organisms. Upon release, they may be found in different body fluids that can be easily accessed via noninvasive methodologies. Due to the unique information encoded in their molecular cargo, they may reflect the state of the parent cell and therefore EVs are recognized as a rich source of biomarkers for early diagnostics involving liquid biopsy. However, body fluids contain a mixture of EVs released by different types of healthy and diseased cells, making the detection of the EVs of interest very challenging. Recent research efforts have been focused on the detection and characterization of diagnostically relevant subpopulations of EVs, with emphasis on label-free methods that simplify sample preparation and are free of interfering signals. Therefore, in this paper, we review the recent progress of the label-free optical methods employed for the detection, counting, and morphological and chemical characterization of EVs. We will first briefly discuss the biology and functions of EVs, and then introduce different optical label-free techniques for rapid, precise, and nondestructive characterization of EVs such as nanoparticle tracking analysis, dynamic light scattering, atomic force microscopy, surface plasmon resonance spectroscopy, Raman spectroscopy, and SERS spectroscopy. In the end, we will discuss their applications in the detection of neurodegenerative diseases and cancer and provide an outlook on the future impact and challenges of these technologies to the field of liquid biopsy via EVs.

Novel Exosome Biomarker Candidates for Alzheimer's Disease Unravelled Through Mass Spectrometry Analysis

Exosomes are small extracellular vesicles (EVs) present in human biofluids that can transport specific disease-associated molecules. Consequently blood-derived exosomes have emerged as important peripheral biomarker sources for a wide range of diseases, among them Alzheimer’s disease (AD). Although there is no effective cure for AD, an accurate diagnosis, relying on easily accessible peripheral biofluids, is still necessary to discriminate this disease from other dementias, test potential therapies and even monitor rate of disease progression. The ultimate goal is to produce a cost-effective and widely available alternative, which can also be employed as a first clinical screen. In this study, EVs with exosome-like characteristics were isolated from serum of Controls and AD cases through precipitation- and column-based methods, followed by mass spectrometry analysis. The resulting proteomes were characterized by Gene Ontology (GO) and multivariate analyses. Although GO terms were similar for exosomes’ proteomes of Controls and ADs, using both methodologies, a clear segregation of disease cases was obtained when using the precipitation-based method. Nine significantly different abundant proteins were identified between Controls and AD cases, representing putative biomarker candidate targets. Among them are AACT and C4BPα, two Aβ-binding proteins, whose exosome levels were further validated in individuals from independent cohorts using antibody-based approaches. The findings discussed represent an important contribution to the identification of novel exosomal biomarker candidates useful as potential blood-based tools for AD diagnosis.

FT-IR Spectral Signature of Sensitive and Multidrug-Resistant Osteosarcoma Cell-Derived Extracellular Nanovesicles

Osteosarcoma (OS) is the most common primary bone cancer in children and adolescents. Despite aggressive treatment regimens, the outcome is unsatisfactory, and multidrug resistance (MDR) is a pivotal process in OS treatment failure. OS-derived extracellular vesicles (EVs) promote drug resistance to chemotherapy and target therapy through different mechanisms. The aim of this study was to identify subpopulations of osteosarcoma-EVs by Fourier transform infrared spectroscopy (FT-IR) to define a specific spectral signature for sensitive and multidrug-resistant OS-derived EVs. EVs were isolated from sensitive and MDR OS cells as well as from mesenchymal stem cells by differential centrifugation and ultracentrifugation. EVs size, morphology and protein expression were characterized. FT-IR/ATR of EVs spectra were acquired in the region of 400–4000 cm⁻¹ (resolution 4 cm⁻¹, 128 scans). The FT-IR spectra obtained were consistently different in the EVs compared to cells from which they originate. A specific spectral signature, characterized by a shift and a new band (1601 cm⁻¹), permitted to clearly distinguish EVs isolated by sensitive and multidrug-resistant OS cells. Our data suggest that FT-IR spectroscopy allows to characterize and define a specific spectral signature for sensitive and MDR OS-derived EVs.

Breast cancer or surrounding normal tissue? A successful discrimination by FTIR or Raman microspectroscopy

Breast cancer is a type of cancer with the highest incidence worldwide in 2021, with early diagnosis and rapid treatment intervention being the reasons for the decreasing mortality rate associated with the disease.

Recent Advances in the Label-Free Characterization of Exosomes for Cancer Liquid Biopsy: From Scattering and Spectroscopy to Nanoindentation and Nanodevices

Exosomes (EXOs) are nano-sized vesicles secreted by most cell types. They are abundant in bio-fluids and harbor specific molecular constituents from their parental cells. Due to these characteristics, EXOs have a great potential in cancer diagnostics for liquid biopsy and personalized medicine. Despite this unique potential, EXOs are not yet widely applied in clinical settings, with two main factors hindering their translational process in diagnostics. Firstly, conventional extraction methods are time-consuming, require large sample volumes and expensive equipment, and often do not provide high-purity samples. Secondly, characterization methods have some limitations, because they are often qualitative, need extensive labeling or complex sampling procedures that can induce artifacts. In this context, novel label-free approaches are rapidly emerging, and are holding potential to revolutionize EXO diagnostics. These methods include the use of nanodevices for EXO purification, and vibrational spectroscopies, scattering, and nanoindentation for characterization. In this progress report, we summarize recent key advances in label-free techniques for EXO purification and characterization. We point out that these methods contribute to reducing costs and processing times, provide complementary information compared to the conventional characterization techniques, and enhance flexibility, thus favoring the discovery of novel and unexplored EXO-based biomarkers. In this process, the impact of nanotechnology is systematically highlighted, showing how the effectiveness of these techniques can be enhanced using nanomaterials, such as plasmonic nanoparticles and nanostructured surfaces, which enable the exploitation of advanced physical phenomena occurring at the nanoscale level.

Exosomal Aβ-Binding Proteins Identified by "In Silico" Analysis Represent Putative Blood-Derived Biomarker Candidates for Alzheimer´s Disease

The potential of exosomes as biomarker resources for diagnostics and even for therapeutics has intensified research in the field, including in the context of Alzheimer´s disease (AD). The search for disease biomarkers in peripheral biofluids is advancing mainly due to the easy access it offers. In the study presented here, emphasis was given to the bioinformatic identification of putative exosomal candidates for AD. The exosomal proteomes of cerebrospinal fluid (CSF), serum and plasma, were obtained from three databases (ExoCarta, EVpedia and Vesiclepedia), and complemented with additional exosomal proteins already associated with AD but not found in the databases. The final biofluids’ proteomes were submitted to gene ontology (GO) enrichment analysis and the exosomal Aβ-binding proteins that can constitute putative candidates were identified. Among these candidates, gelsolin, a protein known to be involved in inhibiting Abeta fibril formation, was identified, and it was tested in human samples. The levels of this Aβ-binding protein, with anti-amyloidogenic properties, were assessed in serum-derived exosomes isolated from controls and individuals with dementia, including AD cases, and revealed altered expression patterns. Identification of potential peripheral biomarker candidates for AD may be useful, not only for early disease diagnosis but also in drug trials and to monitor disease progression, allowing for a timely therapeutic intervention, which will positively impact the patient’s quality of life.

Diagnostic and therapeutic potential of exosomes in Alzheimer's disease

Exosomes are small extracellular vesicles released by almost all cell types in physiological and pathological conditions. The exosomal potential to unravel disease mechanisms, or to be used as a source of biomarkers, is being explored, in particularly in the field of neurodegenerative diseases. Alzheimer's disease (AD) is the most prevalent neurodegenerative disease in the world and exosomes appear to have a relevant role in disease pathogenesis. This review summarizes the current knowledge on exosome contributions to AD as well as their use as disease biomarker resources or therapeutic targets. The most recent findings with respect to both protein and miRNA biomarker candidates for AD, herein described, highlight the state of the art in this field and encourage the use of exosomes derived from biofluids in clinical practice in the near future.