Sex- and Age-Dependent Red Blood Cell Remodeling in Type 2 Diabetes Revealed by FT-IR and Raman Spectroscopy: Part I

Using Fourier transform infrared (FT-IR) spectroscopy and Raman spectroscopy, a research team identified sex- and age-specific molecular alterations in red blood cells from diabetic mice. Spectral analysis revealed protein misfolding, oxidative stress–related membrane destabilization, and lipid remodeling, establishing a non-invasive, label-free platform for molecular staging and monitoring of type 2 diabetes progression.

In the first of a three-part series, Spectroscopy spoke to authors of the resulting paper¹ about how FT-IR differentiates α-helix, β-sheet, and β-turn structures in RBC membrane proteins through analysis of the Amide I and Amide II bands—enhanced by second-derivative processing to reveal subtle protein misfolding in T2DM—while its complementary use with Raman spectroscopy provides a more comprehensive molecular assessment of protein conformation, lipid remodeling, and oxidative stress–induced membrane alterations.

How does FT-IR spectroscopy enable differentiation between α-helix, β-sheet, and β-turn structures in RBC membrane proteins, and why are these distinctions particularly relevant in the context of T2DM?

FT-IR spectroscopy enables differentiation between α-helix, β-sheet and β-turn structures because each conformation establishes a distinct hydrogen-bonding geometry and transition dipole coupling within the peptide backbone, thereby modulating the normal modes of the amide vibrations. These structural differences are primarily reflected in the amide I region of the infrared spectrum, specifically in its band position, shape, and intensity, which are highly sensitive to backbone conformation and thus serve as reliable markers of protein secondary structure even in complex systems such as RBCs. The amide I band, typically spanning the 1600–1700 cm⁻¹ region, is dominated by C=O stretching vibrations of the peptide bond. Distinct sub-bands within this region are associated with different conformations. On the other hand, amide II band falls in the range of 1500-1600 cm⁻¹ and arises from N-H bending and C-N stretching vibrations. It is less specific for secondary structure compared to Amide I but can provide complementary information.

In the context of type 2 diabetes mellitus (T2DM), this structural sensitivity is particularly important. Observed conformational changes are biologically relevant because RBC membrane proteins are key determinants of cell deformability and mechanical stability. Chronic hyperglycaemia and oxidative stress promote gradual protein destabilization in RBC membranes and disturb lipid–protein interactions. Glycation in T2DM introduces rigidity and cross-linking, disturbing normal protein folding.^2.3 Such secondary-structure rearrangements can affect membrane fluidity and receptor function⁴ and further contribute to impaired microcirculation as well as diabetic vascular complications.

Using FT-IR spectroscopy, we observe a characteristic shift from α-helical conformations toward increased β-sheet and β-turn content, a pattern widely associated with protein misfolding and early aggregation. Additionally, formation of β structures in place of α-helix-rich ones has been known to occur in numerous pathological processes.^5,6

What specific information do the Amide I and Amide II bands provide about protein secondary structure, and how does second-derivative analysis enhance the detection of protein misfolding in diabetic RBCs?

As mentioned above, distinct sub-bands within the Amide I region are associated with specific protein conformations. α-helices typically absorb around 1650–1658 cm⁻¹. β-sheets generally appear at lower wavenumbers (1610–1640 cm⁻¹), with the lower end of this range (~1610–1635 cm⁻¹) corresponding to antiparallel β-sheets, while the higher end (~1635–1640 cm⁻¹) may include parallel β-sheets or less ordered β-structures. In antiparallel β-sheet arrangements, a high-frequency component near 1680–1695 cm⁻¹ is often observed. β-turns are typically observed around 1660–1680 cm⁻¹. Using advanced signal processing methods, such as second derivative analysis (described below), individual component bands can be resolved more precisely, enabling discrimination between non-aggregated structures, including α-helix (~1658 cm⁻¹), antiparallel β-sheet (~1631 cm⁻¹), β-turn (~1674 cm⁻¹), and the high-frequency component of antiparallel β-sheet (~1689 cm⁻¹) - and aggregation-associated β-structures. The latter typically include intermolecular hydrated β-sheets (~1612 cm⁻¹) and strongly hydrogen-bonded β-structures appearing at ~1639 cm⁻¹ and ~1700 cm⁻¹, which are commonly linked to β-aggregation. In conventional FT-IR spectra of intact RBCs, signals originating from α-helices, β-sheets, β-turns and unordered structures often overlap extensively, producing broad composite bands that obscure subtle conformational changes. As a result, early-stage misfolding associated with diabetic stress may remain undetectable in raw absorbance spectra. Second-derivative processing suppresses baseline variations and enhances spectral resolution by sharpening individual band components and accentuating inflection points corresponding to hidden sub-peaks. This transformation effectively separates closely overlapping vibrational modes, including both high-intensity bands and lower-intensity features that appear as shoulders. In diabetic RBCs, this allows previously obscured shifts and intensity changes in β-sheet- and random-coil–related components - hallmarks of protein misfolding and aggregation - to be reliably detected.

Moreover, second-derivative spectra reduce the influence of scattering effects and broad background absorption, which are common in intact-cell measurements. This improves spectral reproducibility and facilitates quantitative comparison between control and diabetic samples. When combined with multivariate analysis, derivative-enhanced features provide robust biomarkers of diabetes-induced conformational remodeling. The main limitation of this technique is that it introduces noise by multiplying the number of bands. The interpretation also becomes challenging, as maximums in the raw spectra become minimums in the second derivative.

Consequently, second-derivative analysis enables sensitive, objective detection of protein misfolding in diabetic RBCs by revealing subtle, disease-related alterations in secondary structure that are not apparent in conventional FT-IR spectra, thereby strengthening both mechanistic interpretation and diagnostic discrimination.

In comparing FT-IR and Raman spectroscopy for studying RBCs, what are the complementary strengths of each technique when probing protein conformation, lipid remodeling, and oxidative stress?

FT-IR and Raman spectroscopy provide complementary molecular insights into biological materials, arising from the fundamentally different physical principles underlying each technique. FT-IR spectroscopy exhibits high sensitivity to protein secondary structure, making it particularly effective for probing conformational changes by analyzing the maximum positions and intensity ratios of the Amide I and Amide II bands, allowing detailed assessment of α-helix, β-sheet and β-turn content in complex biological systems. In addition, FT-IR spectroscopy enables precise analysis of lipids: it can identify major lipid classes, is sensitive to the degree of saturation and configuration of double bonds in fatty acids and responds to changes in lipid packing and environmental polarity. As a result, FT-IR spectroscopy allows monitoring of lipid remodeling in cell membranes as well as alterations associated with pathological conditions. In the context of oxidative stress, carbonyl groups formed during lipid and protein oxidation are readily detected in the FT-IR spectrum, serving as an indirect but reliable marker of oxidative damage.

A well-known limitation of FT-IR spectroscopy is its sensitivity to water absorption, which can interfere with measurements in aqueous samples, as well as its lower sensitivity to symmetric vibrational modes. These limitations are effectively addressed by Raman spectroscopy, which provides access to vibrational modes that are weak or inactive in IR, particularly those involving symmetric bonds. Raman spectroscopy is also far less affected by water, making it especially suitable for the analysis of hydrated biological samples. Moreover, Raman spectroscopy enables the identification of specific bands associated with lipid saturation, aromatic amino acid side chains and disulfide bonds, offering valuable insight into lipid organization, protein tertiary structure and redox-related modifications.

While Raman spectroscopy may exhibit lower sensitivity to certain aspects of protein secondary structure and can suffer from fluorescence interference, these drawbacks are well compensated by the strengths of FT-IR spectroscopy. Taken together, FT-IR and Raman spectroscopy form a synergistic, label-free analytical platform, in which FT-IR spectroscopy excels in tracking protein conformational changes, while Raman spectroscopy provides enhanced sensitivity to lipid remodeling and oxidative stress–related molecular features. Their combined use enables a comprehensive molecular characterization of biological samples.

Join us tomorrow for the second part of this interview series, where the authors discuss how FT-IR spectroscopy and Raman spectroscopy detect oxidative stress–related disulfide bond alterations and protein instability in diabetic RBCs, address experimental challenges in resolving membrane versus cytoplasmic protein signals, enable non-invasive molecular profiling beyond conventional assays, and, when coupled with multivariate tools such as oPLS-DA and VIP scoring, enhance robust identification of disease-specific spectral biomarkers.

Acknowledgments

This research was partially funded by the Polish National Science Centre, No. UMO-2020/38/E/ST4/00197. Part of the work was carried out at the Laboratory for Biomedical Spectroscopic Applications (LBSA), Faculty of Pharmacy, Jagiellonian University Medical College. The laboratory infrastructure was co-financed by the European Regional Development Fund under the European Funds for Malopolska 2021–2027 programme (project No.FEMP.01.04-IZ.00-0269/24). The methodologies applied in this study are based on spectroscopic approaches developed by the authors and protected by intellectual property rights, including international and national patent applications: PCT/PL2020/050093, P.436054 and P.43217, as well as a registered trademark (No. Z.493251).

References:

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