Comparing infrared spectroscopic methods for the characterization of Plasmodium falciparum-infected human erythrocytes

Screening of malaria infections in human blood samples with varying parasite densities and anaemic conditions using AI-Powered mid-infrared spectroscopy

BACKGROUND

Effective testing for malaria, including the detection of infections at very low densities, is vital for the successful elimination of the disease. Unfortunately, existing methods are either inexpensive but poorly sensitive or sensitive but costly. Recent studies have shown that mid-infrared spectroscopy coupled with machine learning (MIRs-ML) has potential for rapidly detecting malaria infections but requires further evaluation on diverse samples representative of natural infections in endemic areas. The aim of this study was, therefore, to demonstrate a simple AI-powered, reagent-free, and user-friendly approach that uses mid-infrared spectra from dried blood spots to accurately detect malaria infections across varying parasite densities and anaemic conditions.

METHODS

Plasmodium falciparum strains NF54 and FCR3 were cultured and mixed with blood from 70 malaria-free individuals to create various malaria parasitaemia and anaemic conditions. Blood dilutions produced three haematocrit ratios (50%, 25%, 12.5%) and five parasitaemia levels (6%, 0.1%, 0.002%, 0.00003%, 0%). Dried blood spots were prepared on Whatman™ filter papers and scanned using attenuated total reflection-Fourier Transform Infrared (ATR-FTIR) for machine-learning analysis. Three classifiers were trained on an 80%/20% split of 4655 spectra: (I) high contrast (6% parasitaemia vs. negative), (II) low contrast (0.00003% vs. negative) and (III) all concentrations (all positive levels vs. negative). The classifiers were validated with unseen datasets to detect malaria at various parasitaemia levels and anaemic conditions. Additionally, these classifiers were tested on samples from a population survey in malaria-endemic villages of southeastern Tanzania.

RESULTS

The AI classifiers attained over 90% accuracy in detecting malaria infections as low as one parasite per microlitre of blood, a sensitivity unattainable by conventional RDTs and microscopy. These laboratory-developed classifiers seamlessly transitioned to field applicability, achieving over 80% accuracy in predicting natural P. falciparum infections in blood samples collected during the field survey. Crucially, the performance remained unaffected by various levels of anaemia, a common complication in malaria patients.

CONCLUSION

These findings suggest that the AI-driven mid-infrared spectroscopy approach holds promise as a simplified, sensitive and cost-effective method for malaria screening, consistently performing well despite variations in parasite densities and anaemic conditions. The technique simply involves scanning dried blood spots with a desktop mid-infrared scanner and analysing the spectra using pre-trained AI classifiers, making it readily adaptable to field conditions in low-resource settings. In this study, the approach was successfully adapted to field use, effectively predicting natural malaria infections in blood samples from a population-level survey in Tanzania. With additional field trials and validation, this technique could significantly enhance malaria surveillance and contribute to accelerating malaria elimination efforts.

Exploring the impact of novel thiazole-pyrazole fused benzo-coumarin derivatives on human serum albumin: Synthesis, photophysical properties, anti-cholinergic activity, and interaction studies

Derivatives of thiazole-pyrazole fused benzo-coumarin compounds were successfully synthesized and characterized, followed by a comprehensive spectroscopic investigation on various photophysical properties in different media. The multipronged approach using steady state and time resolved fluorescence spectroscopy pointed out the impact of substitution in the estimated spectroscopic and other physicochemical properties of the systems. Further, the evaluation of anti-acetylcholinesterase (anti-AChE) activity yielded significant insight into the therapeutic potential of the synthesized coumarinyl compounds for the treatment of Alzheimer's disease (AD). The findings revealed a non-competitive mode of inhibition mechanism, with an estimated IC50 value of 67.72 ± 2.00 nM observed for one of the investigated systems as AChE inhibitor. Notably, this value is even lower than that of an FDA-approved AD drug Donepezil (DON), indicating the enhanced potency of the coumarin derivatives in inhibiting AChE. Interestingly, significant diminution in inhibition was observed in presence of human serum albumin (HSA) as evidenced by the relative increase in IC50 value by 8 ∼ 39 % in different cases, which emphasized the role of albumin proteins to control therapeutic efficacies of potential medications. In-depth spectroscopic and in-silico analysis quantified the nature of interactions of the investigated systems with HSA and AChE. Overall, the outcomes of this study provide significant understanding into the biophysical characteristics of novel thiazole-pyrazole fused benzo-coumarin systems, which could aid in the development of new cholinergic agents for the treatment of AD and materials based on coumarin motifs.

Spatially resolved multimodal vibrational spectroscopy under high pressures

In this perspective, we discuss the potential impact on in situ studies under controlled environments of a novel multimodal spectroscopic technique, optical photothermal infrared + Raman spectroscopy, which enables the simultaneous collection of infrared and Raman scattering spectra, along with hyperspectral imaging and chemical imaging with wavelength-independent sub-500 nm spatial resolution. A brief review of the current literature regarding the O-PTIR technique is presented along with recent work from our own lab on determining the crystallinity of soft and inorganic materials. The results highlight the possibility of resolving differences in the crystallinity of soft materials associated with changes in material processing. We also demonstrate the first reported use of a diamond anvil cell with simultaneous infrared and Raman measurements that showcases, using a high energy material as an example, the potential use of O-PTIR spectroscopy in diamond anvil cell techniques.

AFM-IR for Nanoscale Chemical Characterization in Life Sciences: Recent Developments and Future Directions

Despite the ubiquitous absorption of mid-infrared (IR) radiation by virtually all molecules that belong to the major biomolecules groups (proteins, lipids, carbohydrates, nucleic acids), the application of conventional IR microscopy to the life sciences remained somewhat limited, due to the restrictions on spatial resolution imposed by the diffraction limit (in the order of several micrometers). This issue is addressed by AFM-IR, a scanning probe-based technique that allows for chemical analysis at the nanoscale with resolutions down to 10 nm and thus has the potential to contribute to the investigation of nano and microscale biological processes. In this perspective, in addition to a concise description of the working principles and operating modes of AFM-IR, we present and evaluate the latest key applications of AFM-IR to the life sciences, summarizing what the technique has to offer to this field. Furthermore, we discuss the most relevant current limitations and point out potential future developments and areas for further application for fruitful interdisciplinary collaboration.

In silico modeling of patient-specific blood rheology in type 2 diabetes mellitus

Increased blood viscosity in type 2 diabetes mellitus (T2DM) is a risk factor for the development of insulin resistance and diabetes-related vascular complications; however, individuals with T2DM exhibit heterogeneous hemorheological properties, including cell deformation and aggregation. Using a multiscale red blood cell (RBC) model with key parameters derived from patient-specific data, we present a computational study of the rheological properties of blood from individual patients with T2DM. Specifically, one key model parameter, which determines the shear stiffness of the RBC membrane (μ) is informed by the high-shear-rate blood viscosity of patients with T2DM. At the same time, the other, which contributes to the strength of the RBC aggregation interaction (D0), is derived from the low-shear-rate blood viscosity of patients with T2DM. The T2DM RBC suspensions are simulated at different shear rates, and the predicted blood viscosity is compared with clinical laboratory-measured data. The results show that the blood viscosity obtained from clinical laboratories and computational simulations are in agreement at both low and high shear rates. These quantitative simulation results demonstrate that the patient-specific model has truly learned the rheological behavior of T2DM blood by unifying the mechanical and aggregation factors of the RBCs, which provides an effective way to extract quantitative predictions of the rheological properties of the blood of individual patients with T2DM.

Single-cell infrared vibrational analysis by optical trapping mid-infrared photothermal microscopy

Single-cell analysis by means of vibrational spectroscopy combined with optical trapping is a reliable platform for unveiling cell-to-cell heterogeneities in vast populations. Although infrared (IR) vibrational spectroscopy provides rich molecular fingerprint information on biological samples in a label-free manner, its application with optical trapping has never been achieved due to weak gradient forces generated by the diffraction-limited focused IR beam and strong background of water absorption. Herein, we present single-cell IR vibrational analysis that incorporates mid-infrared photothermal (MIP) microscopy with optical trapping. Optically trapped single polymer particles and red blood cells (RBCs) in blood could be chemically identified owing to their IR vibrational fingerprints. This single-cell IR vibrational analysis further allowed us to probe the chemical heterogeneities of RBCs originating from the variation in the intracellular characteristics. Our demonstration paves the way for the IR vibrational analysis of single cells and chemical characterization in various fields.

Optical diffraction tomography and image reconstruction to measure host cell alterations caused by divergent Plasmodium species

Malaria is a life-threatening infectious disease caused by parasites of the genus Plasmodium. Understanding the biological features of various parasite forms is important for the optical diagnosis and defining pathological states, which are often constrained by the lack of ambient visualization approaches. Here, we employ a label-free tomographic technique to visualize the host red blood cell (RBC) remodeling process and quantify changes in biochemical properties arising from parasitization. Through this, we provide a quantitative body of information pertaining to the influence of host cell environment on growth, survival, and replication of P. falciparum and P. vivax in their respective host cells: mature erythrocytes and young reticulocytes. These exquisite three-dimensional measurements of infected red cells demonstrats the potential of evolving 3D imaging to advance our understanding of Plasmodium biology and host-parasite interactions.

Mid-Infrared Photothermal Microscopy: Principle, Instrumentation, and Applications

Midinfrared photothermal (MIP) microscopy, also called optical photothermal infrared (O-PTIR) microscopy, is an emerging tool for bond-selective chemical imaging of living biological and material samples. In MIP microscopy, a visible probe beam detects the photothermal-based contrast induced by a vibrational absorption. With submicron spatial resolution, high spectral fidelity, and reduced water absorption background, MIP microscopy has overcome the limitations in infrared chemical imaging methods. In this review, we summarize the basic principle of MIP microscopy, the different origins of MIP contrasts, and recent technology development that pushed the resolution, speed, and sensitivity of MIP imaging to a new stage. We further emphasize its broad applications in life science and material characterization, and provide a perspective of future technical advances.

Optical photothermal infrared spectroscopy can differentiate equine osteoarthritic plasma extracellular vesicles from healthy controls

Equine osteoarthritis is a chronic degenerative disease of the articular joint, characterised by cartilage degradation resulting in pain and reduced mobility and thus is a prominent equine welfare concern. Diagnosis is usually at a late stage through clinical examination and radiographic imaging, whilst treatment is symptomatic not curative. Extracellular vesicles are nanoparticles that are involved in intercellular communication. The objective of this study was to investigate the feasibility of Raman and Optical Photothermal Infrared Spectroscopies to detect osteoarthritis using plasma-derived extracellular vesicles, specifically differentiating extracellular vesicles in diseased and healthy controls within the parameters of the techniques used. Plasma samples were derived from thoroughbred racehorses. A total of 14 samples were selected (control; n = 6 and diseased; n = 8). Extracellular vesicles were isolated using differential ultracentrifugation and characterised using nanoparticle tracking analysis, transmission electron microscopy, and human tetraspanin chips. Samples were then analysed using combined Raman and Optical Photothermal Infrared Spectroscopies. Infrared spectra were collected between 950-1800 cm^-1. Raman spectra had bands between the wavelengths of 900-1800 cm^-1 analysed. Spectral data for both Raman and Optical Photothermal Infrared Spectroscopy were used to generate clustering via principal components analysis and classification models were generated using partial least squared discriminant analysis in order to characterize the techniques' ability to distinguish diseased samples. Optical Photothermal Infrared Spectroscopy could differentiate osteoarthritic extracellular vesicles from healthy with good classification (93.4% correct classification rate) whereas Raman displayed poor classification (correct classification rate = -64.3%). Inspection of the infrared spectra indicated that plasma-derived extracellular vesicles from osteoarthritic horses contained increased signal for proteins, lipids and nucleic acids. For the first time we demonstrated the ability to use optical photothermal infrared spectroscopy combined with Raman spectroscopy to interrogate extracellular vesicles and osteoarthritis-related samples. Optical Photothermal Infrared Spectroscopy was superior to Raman in this study, and could distinguish osteoarthritis samples, suggestive of its potential use diagnostically to identify osteoarthritis in equine patients. This study demonstrates the potential of Raman and Optical Photothermal Infrared Spectroscopy to be used as a future diagnostic tool in clinical practice, with the capacity to detect changes in extracellular vesicles from clinically derived samples.

Blood Viscosity in Subjects With Type 2 Diabetes Mellitus: Roles of Hyperglycemia and Elevated Plasma Fibrinogen

The viscosity of blood is an indicator in the understanding and treatment of disease. An elevated blood viscosity has been demonstrated in patients with Type 2 Diabetes Mellitus (T2DM), which might represent a risk factor for cardiovascular complications. However, the roles of glycated hemoglobin (HbA_1c) and plasma fibrinogen levels on the elevated blood viscosity in subjects with T2DM at different chronic glycemic conditions are still not clear. Here, we evaluate the relationship between the blood viscosity and HbA_1c as well as plasma fibrinogen levels in patients with T2DM. The experimental data show that the mean values of the T2DM blood viscosity are higher in groups with higher HbA_1c levels, but the correlation between the T2DM blood viscosity and the HbA_1c level is not obvious. Instead, when we investigate the influence of plasma fibrinogen level on the blood viscosity in T2DM subjects, we find that the T2DM blood viscosity is significantly and positively correlated with the plasma fibrinogen level. Further, to probe the combined effects of multiple factors (including the HbA_1c and plasma fibrinogen levels) on the altered blood viscosity in T2DM, we regroup the experimental data based on the T2DM blood viscosity values at both the low and high shear rates, and our results suggest that the influence of the elevated HbA_1c level on blood viscosity is quite limited, although it is an important indicator of glycemic control in T2DM patients. Instead, the elevated blood hematocrit, the enhanced red blood cell (RBC) aggregation induced by the increased plasma fibrinogen level, and the reduced RBC deformation play key roles in the determination of blood viscosity in T2DM. Together, these experimental results are helpful in identifying the key determinants for the altered T2DM blood viscosity, which can be used in future studies of the hemorheological disturbances of T2DM patients.