Single Cell Label-Free Probing of Chromatin Dynamics During B Lymphocyte Maturation

High-Resolution Raman Imaging of >300 Patient-Derived Cells from Nine Different Leukemia Subtypes: A Global Clustering Approach

Leukemia comprises a diverse group of bone marrow tumors marked by cell proliferation. Current diagnosis involves identifying leukemia subtypes through visual assessment of blood and bone marrow smears, a subjective and time-consuming method. Our study introduces the characterization of different leukemia subtypes using a global clustering approach of Raman hyperspectral maps of cells. We analyzed bone marrow samples from 19 patients, each presenting one of nine distinct leukemia subtypes, by conducting high spatial resolution Raman imaging on 319 cells, generating over 1.3 million spectra in total. An automated preprocessing pipeline followed by a single-step global clustering approach performed over the entire data set identified relevant cellular components (cytoplasm, nucleus, carotenoids, myeloperoxidase (MPO), and hemoglobin (HB)) enabling the unsupervised creation of high-quality pseudostained images at the single-cell level. Furthermore, this approach provided a semiquantitative analysis of cellular component distribution, and multivariate analysis of clustering results revealed the potential of Raman imaging in leukemia research, highlighting both advantages and challenges associated with global clustering.

Alterations in lipid metabolism accompanied by changes in protein and carotenoid content as spectroscopic markers of human T cell activation

This work aims to understand better the mechanism of cellular processes accompanying the activation of human T cells and to develop a novel, fast, label-free approach to identify molecular biomarkers for this process. The standard methodology for confirming the activation state of T cells is based on flow cytometry and using antibodies recognizing activation markers. The method provide high specificity detection but may be susceptible to background staining or non-specific secondary antibody reactions. Here, we evaluated the potential of Raman-based molecular imaging in distinguishing non-activated and activated human T cells. Confocal Raman microscopy was performed on T cells followed by chemometrics to obtain comprehensive molecular information, while Stimulated Raman Scattering imaging was used to quickly provide high-resolution images of selected cellular components of activated and non-activated cells. For the first time, carotenoids, lipids, and proteins were shown to be important biomarkers of T-cell activation. We found that T-cell activation was accompanied by lipid accumulation and loss of carotenoid content. Our findings on the biochemical, morphological, and structural changes associated with activated mature T cells provide insights into the molecular changes that occur during therapeutic manipulation of the immune response. The methodology for identifying activated T cells is based on a novel imaging method and supervised and unsupervised chemometrics. It unambiguously identifies specific and unique molecular changes without the need for staining, fixation, or any other sample preparation.

Raman Spectroscopy Profiling of Splenic T-Cells in Sepsis and Endotoxemia in Mice

Sepsis is a life-threatening condition that results from an overwhelming and disproportionate host response to an infection. Currently, the quality and extent of the immune response are evaluated based on clinical symptoms and the concentration of inflammatory biomarkers released or expressed by the immune cells. However, the host response toward sepsis is heterogeneous, and the roles of the individual immune cell types have not been fully conceptualized. During sepsis, the spleen plays a vital role in pathogen clearance, such as bacteria by an antibody response, macrophage bactericidal capacity, and bacterial endotoxin detoxification. This study uses Raman spectroscopy to understand the splenic T-lymphocyte compartment profile changes during bona fide bacterial sepsis versus hyperinflammatory endotoxemia. The Raman spectral analysis showed marked changes in splenocytes of mice subjected to septic peritonitis principally in the DNA region, with minor changes in the amino acids and lipoprotein areas, indicating significant transcriptomic activity during sepsis. Furthermore, splenocytes from mice exposed to endotoxic shock by injection of a high dose of lipopolysaccharide showed significant changes in the protein and lipid profiles, albeit with interindividual variations in inflammation severity. In summary, this study provided experimental evidence for the applicability and informative value of Raman spectroscopy for profiling the immune response in a complex, systemic infection scenario. Importantly, changes within the acute phase of inflammation onset (24 h) were reliably detected, lending support to the concept of early treatment and severity control by extracorporeal Raman profiling of immunocyte signatures.

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.

Dynamically Quantifying Intracellular Elemental Sulfur and Predicting Pertinent Gene Transcription by Raman Spectroscopy in Living Cells

The ability to monitor changes in metabolites and corresponding gene transcription within living cells is highly desirable. However, most current assays for quantification of metabolites or for gene transcription are destructive, precluding tracking the real-time dynamics of living cells. Here, we used the intracellular elemental sulfur in a Thiophaeococcus mangrovi cell as a proof-of-concept to link the quantity of metabolites and relevant gene transcription in living cells by a nondestructive Raman approach. Raman spectroscopy was utilized to quantify intracellular elemental sulfur noninvasively, and a computational mRR (mRNA and Raman) model was developed to infer the transcription of genes relevant to elemental sulfur. The results showed a significant linear correlation between the exponentially transformed Raman spectral intensity of intracellular elemental sulfur and the mRNA levels of genes encoding sulfur globule proteins in T. mangrovi. The mRR model was verified independently in two genera of Thiocapsa and Thiorhodococcus, and the mRNA levels predicted by mRR showed high consistency with actual gene expression detected by real-time polymerase chain reaction (PCR). This approach could enable noninvasive assessment of the quantity of metabolites and link the pertinent gene expression profiles in living cells, providing useful baseline data to spectroscopically map various omics in real time.

Advances in the application of Raman spectroscopy in haematological tumours

Hematologic malignancies are a diverse collection of cancers that affect the blood, bone marrow, and organs. They have a very unpredictable prognosis and recur after treatment. Leukemia, lymphoma, and myeloma are the most prevalent symptoms. Despite advancements in chemotherapy and supportive care, the incidence rate and mortality of patients with hematological malignancies remain high. Additionally, there are issues with the clinical diagnosis because several hematological malignancies lack defined, systematic diagnostic criteria. This work provided an overview of the fundamentals, benefits, and limitations of Raman spectroscopy and its use in hematological cancers. The alterations of trace substances can be recognized using Raman spectroscopy. High sensitivity, non-destructive, quick, real-time, and other attributes define it. Clinicians must promptly identify disorders and keep track of analytes in biological fluids. For instance, surface-enhanced Raman spectroscopy is employed in diagnosing gene mutations in myelodysplastic syndromes due to its high sensitivity and multiple detection benefits. Serum indicators for multiple myeloma have been routinely used for detection. The simultaneous observation of DNA strand modifications and the production of new molecular bonds by tip-enhanced Raman spectroscopy is of tremendous significance for diagnosing lymphoma and multiple myeloma with unidentified diagnostic criteria.

Role of EXO1 nuclease activity in genome maintenance, the immune response and tumor suppression in Exo1D173A mice

DNA damage response pathways rely extensively on nuclease activity to process DNA intermediates. Exonuclease 1 (EXO1) is a pleiotropic evolutionary conserved DNA exonuclease involved in various DNA repair pathways, replication, antibody diversification, and meiosis. But, whether EXO1 facilitates these DNA metabolic processes through its enzymatic or scaffolding functions remains unclear. Here, we dissect the contribution of EXO1 enzymatic versus scaffolding activity by comparing Exo1^DA/DA mice expressing a proven nuclease-dead mutant form of EXO1 to entirely EXO1-deficient Exo1^−/− and EXO1 wild type Exo1^+/+ mice. We show that Exo1^DA/DA and Exo1^–/– mice are compromised in canonical DNA repair processing, suggesting that the EXO1 enzymatic role is important for error-free DNA mismatch and double-strand break repair pathways. However, in non-canonical repair pathways, EXO1 appears to have a more nuanced function. Next-generation sequencing of heavy chain V region in B cells showed the mutation spectra of Exo1^DA/DA mice to be intermediate between Exo1^+/+ and Exo1^–/– mice, suggesting that both catalytic and scaffolding roles of EXO1 are important for somatic hypermutation. Similarly, while overall class switch recombination in Exo1^DA/DA and Exo1^–/– mice was comparably defective, switch junction analysis suggests that EXO1 might fulfill an additional scaffolding function downstream of class switching. In contrast to Exo1^−/− mice that are infertile, meiosis progressed normally in Exo1^DA/DA and Exo1^+/+ cohorts, indicating that a structural but not the nuclease function of EXO1 is critical for meiosis. However, both Exo1^DA/DA and Exo1^–/– mice displayed similar mortality and cancer predisposition profiles. Taken together, these data demonstrate that EXO1 has both scaffolding and enzymatic functions in distinct DNA repair processes and suggest a more composite and intricate role for EXO1 in DNA metabolic processes and disease.

Single-Cell Photothermal Analysis Induced by MoS2 Nanoparticles by Raman Spectroscopy

Two-dimensional nanomaterials, such as MoS2 nanosheets, have been attracting increasing attention in cancer diagnosis and treatment, thanks to their peculiar physical and chemical properties. Although the mechanisms which regulate the interaction between these nanomaterials and cells are not yet completely understood, many studies have proved their efficient use in the photothermal treatment of cancer, and the response to MoS2 nanosheets at the single-cell level is less investigated. Clearly, this information can help in shedding light on the subtle cellular mechanisms ruling the interaction of this 2D material with cells and, eventually, to its cytotoxicity. In this study, we use confocal micro-Raman spectroscopy to reconstruct the thermal map of single cells targeted with MoS2 under continuous laser irradiation. The experiment is performed by analyzing the water O-H stretching band around 3,400 cm−1 whose tetrahedral structure is sensitive to the molecular environment and temperature. Compared to fluorescence-based approaches, this Raman-based strategy for temperature measurement does not suffer fluorophore instability, which can be significant under continuous laser irradiation. We demonstrate that irradiation of human breast cancer MCF7 cells targeted with MoS2 nanosheets causes a relevant photothermal effect, which is particularly high in the presence of MoS2 nanosheet aggregates. Laser-induced heating is strongly localized near such particles which, in turn, tend to accumulate near the cytoplasmic membrane. Globally, our experimental outcomes are expected to be important for tuning the nanosheet fabrication process.

Towards Raman-Based Screening of Acute Lymphoblastic Leukemia-Type B (B-ALL) Subtypes

Simple Summary

Acute lymphoblastic leukemia (ALL) is the most common pediatric malignancy originating from abnormal lymphoid progenitor cells. Since ALL is genetically highly heterogenous, more sensitive and rapid methods for identifying the molecular subtype of ALL are still being searched, and Raman spectroscopy (RS) has a chance of becoming a valuable tool for this purpose. Herein, the RS was applied to analyze normal B cells and three subtypes of B-ALL, characterized by the presence of the product of gene fusion, i.e., BCR-ABL1, TEL-AML1, and TCF3-PBX1. The classification and discrimination of normal and neoplastic cells were carried out with the chemometric approach. Normal B cells were characterized mostly by bands assigned to nucleic acids and proteins, whereas three subtypes of ALL appeared to contain a higher lipid content. Spectral differences between particular ALL subtypes were modest. The results lead to the conclusion that RS has the potential as a diagnostic tool in clinical practice.

Abstract

Acute lymphoblastic leukemia (ALL) is the most common type of malignant neoplasms in the pediatric population. B-cell precursor ALLs (BCP-ALLs) are derived from the progenitors of B lymphocytes. Traditionally, risk factors stratifying therapy in ALL patients included age at diagnosis, initial leukocytosis, and the response to chemotherapy. Currently, treatment intensity is modified according to the presence of specific gene alterations in the leukemic genome. Raman imaging is a promising diagnostic tool, which enables the molecular characterization of cells and differentiation of subtypes of leukemia in clinical samples. This study aimed to characterize and distinguish cells isolated from the bone marrow of patients suffering from three subtypes of BCP-ALL, defined by gene rearrangements, i.e., BCR-ABL1 (Philadelphia-positive, t(9;22)), TEL-AML1 (t(12;21)) and TCF3-PBX1 (t(1;19)), using single-cell Raman imaging combined with multivariate statistical analysis. Spectra collected from clinical samples were compared with single-cell spectra of B-cells collected from healthy donors, constituting the control group. We demonstrated that Raman spectra of normal B cells strongly differ from spectra of their malignant counterparts, especially in the intensity of bands, which can be assigned to nucleic acids. We also showed that the identification of leukemia subtypes could be automated with the use of chemometric methods. Results prove the clinical suitability of Raman imaging for the identification of spectroscopic markers characterizing leukemia cells.