Skip to main content

Course of Plasmodium infection studied using 2D-COS on human erythrocytes



The threat of malaria is still present in the world. Recognizing the type of parasite is important in determining a treatment plan. The golden routine involves microscopic diagnostics of Giemsa-stained thin blood smears, however, alternative methods are also constantly being sought, in order to gain an additional insight into the course of the disease. Spectroscopic methods, e.g., Raman spectroscopy, are becoming increasingly popular, due to the non-destructive nature of these techniques.


The study included patients hospitalized for malaria caused by Plasmodium falciparum or Plasmodium vivax, in the Department of Infectious Diseases at the University Hospital in Krakow, Poland, as well as healthy volunteers. The aim of this study was to assess the possibility of using Raman spectroscopy and 2D correlation (2D-COS) spectroscopy in understanding the structural changes in erythrocytes depending on the type of attacking parasite. EPR spectroscopy and two-trace two-dimensional (2T2D) correlation was also used to examine the specificity of paramagnetic centres found in the infected human blood.


Two-dimensional (2D) correlation spectroscopy facilitates the identification of the hidden relationship, allowing for the discrimination of Raman spectra obtained during the course of disease in human red blood cells, infected by P. falciparum or P. vivax. Synchronous cross-peaks indicate the processes taking place inside the erythrocyte during the export of the parasite protein towards the cell membrane. In contrast, moieties that generate asynchronous 2D cross-peaks are characteristic of the respective ligand-receptor domains. These changes observed during the course of the infection, have different dynamics for P. falciparum and P. vivax, as indicated by the asynchronous correlation cross-peaks. Two-trace two-dimensional (2T2D) spectroscopy, applied to EPR spectra of blood at the beginning of the infection, showed differences between P. falciparum and P. vivax.


A unique feature of 2D-COS is the ability to discriminate the collected Raman and EPR spectra. The changes observed during the course of a malaria infection have different dynamics for P. falciparum and P. vivax, indicated by the reverse sequence of events. For each type of parasite, a specific recycling process for iron was observed in the infected blood.

Graphical Abstract


Malaria is one of the most dangerous infectious diseases [1]. Currently, it occurs in Poland as a disease imported from endemic regions [2]. Malaria is a mosquito-borne vector disease, caused by five species of parasite that are pathogenic to humans. Most malaria cases and deaths are thought to be caused by the Plasmodium falciparum infection [1]. Recently, however, it has been identified that the Plasmodium vivax infection and its consequences may have been underestimated and are, therefore, also life-threatening [3].

Malaria is a blood disease due to the tissue in which it develops. The parasites attack red blood cells, but not at random. Plasmodium falciparum can invade all erythrocyte subsets, while P. vivax preferentially invade immature red blood cells or, reticulocytes [4]. The life cycle of parasites in humans in the pre-erythrocytic stage is slightly different; it is 10 days and 12 days, respectively, for P. falciparum and P. vivax. Additionally, the dormancy of P. vivax hypnozoites varies over time, depending on the geographic location [5]. The 48-h development cycle in the host cell for both types of Plasmodium is similar; this includes around 20 h as a ring stage, then approximately 20 h as a trophozoite stage and finally around eight hours as a schizont. Parasites slightly differentiate the intra-erythrocyte development of gametocytes; in the case of P. falciparum, this process takes 15 days, and for P. vivax only 4 days [6, 7]. Anyone with a fever, returning from an endemic area, should have malaria in the differential diagnosis. The gold standard of diagnostics is the parasitological examination of Giemsa-stained capillary blood.

The aim of this study was to assess the possibility of using Raman spectroscopy in understanding certain structural changes in erythrocytes, depending on the type of the attacking parasite. The work to date on distinguishing the effect of parasites on blood cells using statistical methods has been promising [8]. 2D correlation analysis was also chosen because it was successful in understanding the aging process of healthy red blood cells and identifying the specific aging of cells infected with P. falciparum [9,10,11]. Moreover, in the presented studies, EPR measurements were made to check whether it is possible to identify infected blood according to the species of Plasmodium and by using magnetic methods. Identifying the disease-causing species is of clinical importance, therefore, it is important in diagnostics.


Blood samples

The spectroscopic measurements were carried out on blood samples collected from patients at the Department of Infectious Diseases, University Hospital in Kraków, Poland, who had been diagnosed with malaria caused by P. falciparum or P. vivax, as well as healthy volunteers. The blood of five patients from each infected group, with comparable parasitaemia, was taken for Raman and EPR analysis.

The blood from patients diagnosed with malaria was obtained by venipuncture. The blood was immediately transported to the Raman laboratory in specialized tubes containing heparin as an anticoagulant. A smear was then made, but to measure it, the cells were allowed to stabilize for approximately 10 min. Raman spectroscopic measurements were performed on the first, fifth and tenth day of hospitalization; the last day was characterized by negative parasitological test results.

Statistical analysis of standard laboratory tests

In order to check whether there are statistically significant differences in standard medical tests between two groups of malaria patients, the Mann–Whitney U test was used. The following descriptive statistics were included in the statistical analysis: mean (M), standard deviation (SD), minimum (Min), maximum (Max), median (Me), first (Q1) and third quartile (Q3). A statistical analysis was performed using Statistics 25 software (IBM SPSS, USA). The threshold of statistical significance included values of p < 0.05.

Raman microspectroscopy

A Renishaw InVia spectrometer, working in a confocal mode, connected to a Leica optical microscope with a 100× magnification objective (NA = 0.9) and an argon laser line of 514.5 nm were used to measure single erythrocytes. The laser power was kept low, ca. 1–3 mW at the sample, to ensure minimum invasion into the cells. The averaged spectra were made in Thermo Scientific Omnic v. 9.3 software.

EPR spectroscopy

EPR measurements were performed using an X-band Bruker ELEXSYS 500 spectrometer (Karlsruhe, Germany) with 100 kHz field modulation. The samples of P. falciparum and P. vivax-infected whole blood, collected at the beginning of hospitalization, as well as the blood of healthy volunteers, were sealed in EPR tubes and the spectra were recorded at 77 K with a modulation amplitude of 0.5 mT.

2D-COS analysis

Generalized 2D correlation analysis was performed using the Noda’s method [12, 13]. The averaged spectra for all of the measured erythrocytes of 10 patients (five infected with P. falciparum and five with P. vivax) on the first, fifth and tenth day of hospitalization were considered as so-called dynamic spectra. The time of hospitalization was regarded as an external perturbation. The analysed spectra were pre-processed: smoothed, baseline corrected and normalized with the Renishaw WiRE 3.4 and 2.0 software and subjected to 2D correlation analysis.

EPR spectra of the Plasmodium infected at the beginning of the infection process and healthy infected whole blood constituted an input data for generating 2T2D correlation maps [14]. The software package for the calculation and presentation of the 2D spectra is built into the Win-IR Pro (Bio-Rad) software.

Results and discussion

The results of statistical analysis of standard laboratory tests

The analysis concerns the comparison of two groups of patients diagnosed with malaria species, 65.6% of cases (n = 21) were P. falciparum and 21.9% (n = 7) were P. vivax. No statistically significant differences were observed between the two groups of patients, see Table 1.

Table 1 Descriptive statistics on the analyzed parameters in a group of patients diagnosed with P. vivax and P. falciparum malaria (The Mann–Whitney U test)

The Raman microspectroscopy of malaria-infected single human RBC

The activity of parasites changes the size and shape of red blood cells in a characteristic way. One of the observed features is the loss of the biconcave shape of the blood cell, see Fig. 1A. The blood of patients from malaria-infected groups was characterized by comparable parasitaemia. P. falciparum and P. vivax parasitaemia was 3.2 (0.27%) and 3.0 (0.2%), respectively. Raman spectroscopy enables the monitoring of haem modification taking place in the intra-erythrocytic phase of the Plasmodium life cycle [15]. The most characteristic is the shift of the ν4 band in the course of hospitalization from approximately 1360 cm−1 on the first day of hospitalization to 1373 cm−1 and 1371 cm−1 on the last day of hospitalization for P. falciparum and P. vivax, respectively (see Table 2). There is also a slight shift of haem ν37 vibration from positions 1586 cm−1 and 1585 cm−1 to 1587 cm−1 and 1586 cm−1 in the course of hospitalization for P. falciparum and P. vivax, respectively. In the case of both species, there is also a clearly visible increase in the ν10 band over the course of recovery. However, despite these minimal differences, the spectra of Plasmodium-infected red blood cells, at the same stage of the disease, are quite similar, see Figs. 1B, 2A and B. Due to this, it is difficult to determine the differentiating features, related to a specific species of parasite, directly from the spectra of erythrocytes. The noticeably higher background intensity observed in the spectra during the course of infection for P. vivax compared to P. falciparum is noteworthy, see Fig. 2C. The background intensity was determined for the wavenumber of 2000 cm−1 assuming a linear background course, as indicated in Fig. 2A and B. The elevated background appears to be a signal of inflammation in the body. It transpired that the background for the three analysed time periods in the course of infection is higher for P. vivax, see Fig. 2C [16]. The inflammatory response is related to the activation of signaling pathways that increase inflammation and the electron density in tissues and blood cells [17, 18]. Inflammation appears to last longer and recurs in the months following infection in P. vivax [19].

Fig. 1
figure 1

A microphotographs of the erythrocytes of healthy volunteers and malaria-infected erythrocytes with P. falciparum and P. vivax and with trophozoites in the form of a ring; B Raman spectra showing the most prominent peaks of the erythrocytes of healthy volunteers, infected with P. falciparum and P. vivax, in the range of 3200–300 cm−1. The values of the bands for healthy blood cells are marked. Excitation laser line at 514.5 nm; 100× magnification objective (NA = 0.90)

Table 2 Observed major Raman bands [cm−1] and their assignments for single human RBC: healthy, P. falciparum and P. vivax infected excited using 514.5 nm laser line
Fig. 2
figure 2

Averaged Raman spectra of all erythrocytes of five patients in each group, on the first, fifth and tenth day of hospitalization, A P. falciparum, B P. vivax, C the background intensity is determined for the wavenumber of 2000 cm−1 assuming a linear background, vide (A) and (B)

2D correlation of malaria-infected single human RBC, infected with Plasmodium

Due to the similarity of the spectra of Plasmodium- infected red blood cells, at the same stage of the disease, by different species of Plasmodium, 2D correlation analysis (2D-COS) was performed to find hidden relationships. Construction of the two-dimensional spectrum (2D-COS) uses time-dependent fluctuations of spectroscopic signals, that change during treatment [12]. 2D-COS correlation spectroscopy is particularly helpful when disturbances in the studied systems are characterized by low variability, i.e. low amplitude. The 2D spectra obtained by this method, consisting of two types of dependency, synchronous and asynchronous, can highlight useful information often buried in the original time-resolved spectra. They are expressed in terms of the real and imaginary components of the Fourier transform of the dynamic spectrum.

2D synchronous correlation

Peaks in the synchronous correlation spectrum indicates the susceptibility of simultaneous or coincidental spectral intensity response of the selectively excited various chemical moieties of the system. In this work in effect gives you the susceptibility of spectral intensity changes reflecting various molecular moieties along the time course of infection. The synchronous 2D correlation, conducted for the Raman spectra obtained during the course of hospitalization due to infection with two types of Plasmodium, showed almost identical, relationships, which can be seen in the 2D spectra in Fig. 3A and B, covering the range of 3200–600 cm−1. The autopeaks show the greatest variability of spectral intensity in the so-called dynamic spectra; they were collected with assignments, shown in Tables 2 and 3.

Fig. 3
figure 3

Synchronous 2D correlation of Raman spectra of malaria-infected erythrocytes on the first, fifth and tenth day of hospitalization. A P. falciparum, and B P. vivax, in the wavenumber range of 3200–600 cm−1; C P. falciparum, and D P. vivax, in the wavenumber range of 1750–900 cm−1, vide (A), and (B) excitation of 514.5 nm

Table 3 The prominent synchronous correlation cross-peaks for P. falciparum infected RBCs and their assignments, 514.5 nm laser line [8,9,10, 15, 22, 27, 34,35,36,37, 41]

An intense autopeak was observed for both types of Plasmodium for the band around 2930 cm−1, which indicates the importance of sCH3 vibration, including membrane lipids, in particular, phosphatidylcholine (PC) [20]. PC is a component of the outer part of the erythrocyte lipid bilayer, which is significantly altered by parasite attack [21]. Further intense autopeaks appearing for the wavenumbers 1641, 1585, 1360 cm−1 (P. falciparum) and 1638, 1585, 1361 cm−1 (P. vivax) can be mainly attributed to haem marker vibrations and also to haemozoin [15, 22]. However, in addition, the vibrations at approximately 1640 cm−1 are also due to the helical conformation of amide I [23]. It seems that domains consisting of bundles of helices or mixed helix-sheet structures of parasitic proteins, participating in the invasion of the parasite into the cell, also make a significant contribution to this peak [24,25,26]. Moreover, the strong aspartic acid (Asp) band assigned to the ionized carboxyl groups adds its contribution to the 1584 cm−1 autopeak [27]. One cannot exclude the participation of histidine (His) νC4 = C5 stretching vibrations in this peak, which occurs across a wide range of 1573–1590 cm−1, indicating the number of protonated nitrogen atoms and metal ion bonding [28]. Another autopeak in the vicinity of 1360 cm−1 is also generated by tryptophan (Trp) residues and indicates the importance of this amino acid in the action of the parasite on red blood cells. Trp is characterized by a spectroscopic doublet of 1360/1340 cm−1 Raman bands (the so-called W7). The dominance of the 1360 cm−1 band of the W7 doublet indicates the hydrophobicity of the environment in which the Trp amino acid residue is located [29].

A comparison of the two synchronous 2D correlation maps, shown in Fig. 3, revealed slight relative differences in positions and intensities between the cross-peaks of cells infected with P. falciparum and P. vivax. All synchronous cross peaks, regardless of Plasmodium species, are positive, see Fig. 3A, B, C and D.

Fig. 4
figure 4

Asynchronous 2D correlation of Raman spectra of malaria-infected erythrocytes on the first, fifth, and tenth day of hospitalization. A P. falciparum and B P. vivax, in the wavenumber range of 3200–600 cm−1; C P. falciparum, and D P. vivax, in the wavenumber range of 1750–900 cm−1, vide (A) and (B) excitation of 514.5 nm

The intense synchronous cross-peaks for P. falciparum come from 2885 cm−1asCH2, PC) and 1577 cm−1 (from νC = C of His vibration) both correlates with phosphatidylethanolamine (PE) νsCH3 vibration (approximately 2940 cm−1) (see Fig. 3A, and Table 3). The appearance of PC and PE derived cross-peaks in infected blood cells may be related to the developmental stages of the parasite life cycle. The greatest fluidization of the erythrocyte membrane domains, occupied by PC and PE, occurs at the beginning of the infection between the ring stage and the trophozoite stage of the parasite [30]. Vibrations of the Trp and His residues generate a series of synchronous cross-peaks in the spectra of infected blood cells, especially among cells infected with P. falciparum, see Table 3. This set of cross-peaks indicates the appearance of the HRP2 protein (histidine-rich protein 2) in the infected cell, which is a soluble protein in the medium, bound to the erythrocyte membrane and secreted quickly, two hours after invasion [31, 32]. Other intense synchronous cross-peaks are also generated by His νC = C vibrations (around 1590 cm−1) and haem vibrations, ν13 or ν42 (1229 cm−1), ν30 (1171 cm−1) and ν47 (1002 cm−1). A relatively low intensity, positive cross-peak at (676,1587) indicates the correlation of the νCS vibrations (of cysteine, Cys) with the ν37 haem vibrations [33].

Intense synchronous cross-peaks for red blood cells infected with P. vivax arise from the correlation of vibrations νsCH3 (2943 cm−1) typical of lipids in the internal membrane layer, and νC = C from His (1581 cm−1), see Table 4. There are also several synchronous cross-peaks that correlate the vibrations of Trp (W7, at c.a.1360 cm−1) with the vibration of the haem, ν37 and with His νC4 = C5 (1587 cm−1). The rocking vibrations of the NH3, τ(NH3) groups in threonine (Thr), with a wavenumber of around 1120 cm−1, generate an asynchronous peak with the ν37 of the haem vibrations in the case of P. vivax [34]. The other synchronous cross peaks correlate with the vibrations characteristic of the haem, such as ν37 and ν10, ν30 and ν37, ν22 and ν37 and His. Finally, positive cross-peaks correlate the vibrations of 518 cm−1 skeletal vibrations of Cys SS and the 745 cm−1 vibrations of Thr, valine (Val) and serine (Ser) with the vibrations ν37 (1587 cm−1) of haem and His [33, 35,36,37].

In summary, synchronous cross-peaks reflect the activity of the parasite, which produces and then exports many of its proteins, the most important being PfHRP2 and PvRBP, for P. falciparum and P. vivax, respectively, to the erythrocytes cytosol and its membrane [38]. Therefore, synchronous cross-peaks characterize the parasite-haem connections inside the blood cell during protein export to the cell membrane [32, 39]. Participation in the creation of cross-peaks by haemozoin and amino acids, mainly His, indicates the function of parasite proteins, e.g., PfHEP2. Plasmodium- derived PfHEP2 protein, which is involved in haem detoxification, contains 60–70% His and alanine (Ala) residues. When the parasite transforms into the trophozoite stage, it captures around 40% of the blood cell volume. The host cell surface becomes covered with small knobs in which there is a parasite knob-associated, histidine-rich protein (KAHRP) or Trp-rich PfEMP1 (P. falciparum erythrocyte membrane protein 1) and the surface becomes parasitic in origin [24, 40].

2D asynchronous correlation

The signs of asynchronous cross peaks provides the sequential order of intensity changes of different constituents. Therefore, on asynchronous maps, attention is drawn to a group of asynchronous cross-peaks that appear within a similar range of wave numbers but have the opposite sign, indicating a different sequence of events influencing their generation, see Fig. 4A and B. Identifying just some of the intense cross peaks for P. falciparum, there are cross-peaks that correlate the vibrations of the membrane lipids, in which changes in the inner membrane layer (PE, at c.a 2945 cm−1) are later than that in haem ν4 (at 1356 cm−1) and ν37 (at 1581 cm−1), see Table 3. A series of negative cross peaks correlates the ν10 vibration at 1642 cm−1 (corresponding to changes in haemozoin, as well as in the secondary structure of helical proteins, also in parasitic proteins) and are ahead of the changes represented by the ν19 haem vibrations, together with tyrosine (Tyr) (1609 cm−1), His (1573 cm−1) and lysine (Lys) (1530 cm−1) [22, 24, 25, 28, 41]. The vibrations of ν4 in the deoxy-structure and that of Trp residue (1360 cm−1) correlates positively with the ν10 of haemozoin (1642 cm−1) [22, 28]. On the other hand, the vibration of ν4 in the deoxy-structure (1359 cm−1), also coinciding with the Trp position, correlates asynchronously and negatively with the ν4 vibration characterizing the oxidized haem structure (1374 cm−1) [15, 28]. Interesting are two negative cross-peaks, generated by the ν4 vibration of the haem deoxy- structure, (−(1359,1573)) and (−(1359,1535)). The first is derived from the ν4 of haemozoin with Asp and His (1573 cm−1), while the N–H bending vibration in the plane and the C–N stretching vibration for Lys (1535 cm−1) generates a second asynchronous peak for P. falciparum [28, 41].

There are also many asynchronous cross-peaks observed in red blood cells infected with P. vivax; it is worth mentioning a few intense cross-peaks generated by the vibrations of membrane lipids, see Fig. 4B and D. The peak generated by the νsCH2 (PC) vibrations (2852 cm−1) correlates asynchronously with vsCH3 (PE) (2938 cm−1) [23]. Another positive cross-peak correlates the vibrations of Lys(1527 cm−1) with the vibrations of PE (2936 cm−1) belonging to the inner monolayer, see Table 4 [23, 41]. The next two negative peaks, the first correlating His (1630 cm−1) with amide I of conf-β (1664 cm−1) and the second cross-peak correlating haemozoin ν10 vibration (1639 cm−1) with amide I of the antiparallel β-sheet conformation (1696 cm−1) signify intense membrane modification through possible invasion pathway formation [42]. The band at 1696 cm−1, indicating the νC = O stretching vibrations of non-hydrated C = O groups of Asp residue, is a sign of aspartic proteinase activity [27, 43]. The hydrophobicity of the environment in which the Trp residue is located, is confirmed by the intense indole band for the first overtone νW18 at ca. 1515 cm−1, which is preceded by changes in haemozoin v10 [22, 28]. The presence of this positive asynchronous cross-peak illustrates the changes taking place in the host receptor under the influence of interaction with the parasite proteins (of amide I conf- α) and with the haem detoxification product, haemozoin [40].

There are two pairs of negative cross-peaks that are derived from vibrations of molecular groups that differ slightly, for P. falciparum at –(1609,1642) and –(1573,1642), while for P. vivax at –(1619,1642) and –(1591,1642), see Tables 3 and 4. These cross-peaks are generated by the 1642 cm−1 of the haemozoin v10 and peptide bond vibrations of conf-α, derived from the helical structures of the Plasmodium proteins, i.e., PfRH5 and PvRBP2, see Tables 3 and 4 [44, 45]. These vibrations precede subsequent events that are connected and correlate the moieties of characteristic amino acids, forming the respective ligand-receptor binding domains, i.e., Tyr and Asp and/or His in case of P. falciparum, and Tyr and/or Trp and Tyr and/or His for P. vivax [23, 28, 36]. Parasite ligand variation in expression makes analysis and diagnosis difficult [46].

Table 4 The prominent synchronous correlation cross-peaks for P. vivax infected RBCs and their assignments, 514.5 nm laser line [8,9,10, 15, 22, 27, 34,35,36,37, 41]

The reverse sequence of events for both types of Plasmodium is clearly visible on the asynchronous maps, see Fig. 4. In relation to P. falciparum, a negative asynchronous cross-peak appears −(1530,1642), while in the case of P. vivax, this is positive +(1515,1642). Regarding the first P. falciparum cross-peak, changes occur in amide I conf-α and in haemozoin, which correlate with the subsequent changes in Lys and His residues [23, 28, 41]. In the case of the second P. vivax positive cross-peak, the changes begin with Tyr and/or Trp that cause the rearrangement of amide I conf- α vibrations [28, 36].

The second pair of intriguing cross-peaks with opposite signs indicates: positive +(1360,1642) for P. falciparum and negative –(1357,1642) for P. vivax. Vibrations with a wave number of 1360 cm−1 for P. falciparum are caused due to changes in Trp, proving that this takes place in a hydrophobic environment [28]. As regards the second cross-peak, the 1357 cm−1 vibrations, assigned to ν4 haem, follow signals from the haemozoin and/or parasite protein secondary structure vibrations [22]. The difference in the position of the Trp band, observed in erythrocytes infected with different types of parasites, indicates a different positioning of this amino acid residue relative to the haem [28]. This, in turn, indicates a different pathway of vibrational energy flow for both parasite infections [47]. It can be concluded that the dynamics observed in these cross-peaks represent the initial invasion stage in both these cases [39].

These two pairs of intense asynchronous cross-peaks seem very indicative. They reflect the process and specificity of the formation of the transmembrane complex of the parasite ligand and the host cell receptor. PfRH5 consists of two helical bundles and some amino acid residues (mostly His) that are aligned with the basigin receptor binding site [44]. Basigin has evolved two ways of binding. In trans-recognition, basigin attaches soluble protein or protein on an adjacent cell. In cis-recognition, basigin binds to proteins in the same cell, especially in the same membrane [48]. The presence of the conf. α-rich proteins of the parasite is indicated by a vibration at position 1642 cm−1, which together with the vibration of Trp residues around 1360 cm−1 indicates the hydrophobic nature of pockets on the basigin, generating a positive asynchronous correlation peak (see Table 3) [49, 50]. Amino acids such as His, Trp, Tyr, and Lys, which generate cross peaks for P. falciparum, indicate their involvement in the formation of the PfRh5-basigin complex [49].

The corresponding complex for P. vivax invasion uses transferrin receptor (TfR) as the host receptor, as indicated by the higher rates of parasite invasion into young reticulocytes, which have a high level of TfR [39]. This is consistent with the observed cross-peaks from the amino acids, Asp, Tyr and His, characteristic of the iron binding site (see Table 4) [51]. It is worth noting that on 2D spectra for the P. vivax infection, there are asynchronous cross-peaks in which νSS vibrations from Cys residues are involved (see Table 4) [33]. This indicates that PvRBPs, which are rich in cysteine residues, build up important interactions [26]. In this context, peak +(519,2953) indicates the effect of PvRBP Cys- rich domains on changes in the host’s biological membrane (see Table 3) [30].

Involvement in gametocyte formation after early reticulocyte invasion has also been reported, which may be an additional reason for the generation of the observed differences in the sequence of events in the 2D correlation spectra [39]. The full development of P. falciparum gametocytes takes place simultaneously in the erythrocyte phase of the parasite's life cycle and proceeds through a series of intermediate stages, lasting up to 9–12 days. [52]. A factor that may contribute to the initiation of this process may be, for example, contact with anti-malarial drugs that are used in hospital conditions. Such external stimuli can lead to an increased tendency to produce gametocytes [6].

Whole blood EPR spectroscopy

The paramagnetic centers, the signal of which can be expected in human blood, are compounds of iron and copper and also free radicals (see Table 5) [53, 54]. EPR spectra depend on the local symmetry in which the paramagnetic center is located, as well as on the oxidation and spin state, therefore, they provide information regarding the surroundings of the ion with paramagnetic properties [55]. Hence, the task was to verify which changes occur in the blood, due to the activity of the malaria parasite. The EPR spectra of the healthy blood (upper spectrum), P. falciparum-infected blood (middle spectrum) and P. vivax-infected (lower spectrum) at the beginning of hospitalization are presented in Fig. 5A. Spectra in the narrower ranges of magnetic fields are shown in Fig. 5B–D, respectively. The range of resonant fields from 900 to 2000 Gs includes the characteristic signals from ferric haem, while the ferrous haem is undetectable (see Fig. 5B). Ferric compounds of a high-spin of 5/2 are characterized by a distinctive g- factor of around 6.0. The third g-factor component of this methaemoglobin signal appears around 2 and is hidden under the other visible signals in this region, see Fig. 5D [56]. The fragment of the EPR spectrum from healthy blood, shown in Fig. 5B in the inset, with characteristic g-values of 6 and 5.80, is analogous to the typical signal observed for the iron of isolated alpha-haemoglobin chains [57]. This signal is not observed in the case of Plasmodium-infected blood, as shown in Fig. 5B.

Table 5 Observed EPR resonance signals and their assignments for healthy and Plasmodium infected human whole blood, at 78 K, X-band
Fig. 5
figure 5

EPR spectra of human whole blood measured in the X-band of: A healthy blood (upper spectrum), P. falciparum-infected blood (middle spectrum) and P. vivax infected blood (lower spectrum) both at the beginning of hospitalization, in the magnetic field range of 600–5600 Gs; B 900–2000 Gs; C 2000–3500 Gs; D 3000–5000 Gs

In the region of the g-factor 4.10–4.40, a characteristic signal is visible, observed for Fe3 + in non-haem proteins [58]. These signals, indicating paramagnetic centers of rhombic symmetry for normal blood and blood infected with P. falciparum and P. vivax do not differ from one other, see Fig. 5C. These anisotropic signals can be attributed to the high-spin ferric ions found in transferrin.

Regarding healthy as well as infected blood, a very wide band develops in the next range of magnetic fields, for g = 2.30–2.90, see Fig. 5C. This range is characterized by low-spin, ferri-haem centres [59]. The characteristic broadband profile at 78 K indicates that it may be composed of phases typical of iron storage proteins [60]. Therefore, signals of this type have been classified, among others, as iron aggregates, possibly in ferritin. The maximum of this broad signal has clearly shifted in the case of the infected blood compared to healthy blood, and as regards the infected blood, the maximum depends on the type of parasite, see Fig. 5C. The maximum band for blood infected with P. falciparum is g = 2.78, and for P. vivax is g = 2.88. This broad band probably comes from overlapping low- and high-spin iron centers with different local symmetries [56, 61].

Figure 5D shows the signal g = 1.92 for EPR spectra of healthy blood, typical of low-spin, ferri-haem complexes [59]. Basically, this spectral range describes copper centers with tetragonal symmetry, as indicated by the characteristic coefficient, g = 2.05 [62].

In this range, narrow signals around 3000 Gs are also clearly visible. Biological EPR signals with g-factors close to 2 are usually interpreted as free radicals [63] and peroxyl radicals are generated by hydrogen peroxide in haem proteins [64]. The signal with g = 2.01, observed in healthy blood, can be attributed to this radical [65, 66]. The second radical signal with g = 2.002 in the infected blood comes from the tyrosyl radical. It was found that the g-factor characterizing the tyrosyl radical is sensitive to local charge densities, hence the differences in radical formation should match the different protein structures [67,68,69].

Pathologies are an additional factor influencing the formation of radicals [64, 70]. In fact, human red blood cells, infected with the trophozoite, P. falciparum, produce around twice as many H2O2 and OH radicals than normal erythrocytes. This characteristic was not observed at the ring stage when digestion of the host cells had not yet begun. Therefore, it is believed that reactive oxygen species are produced in the parasite's food vacuole during the digestion of the host cell's cytosol and, therefore, remain in the host cell [71].

2T2D correlation of whole blood infected with Plasmodium

Two-trace two-dimensional correlation spectroscopy (2T2D), gives the possibility to compare a pair of spectra in the formalism of two-dimensional correlation as a 2D map [14]. This analysis allows preferentially to indicate similarities or differences of blood samples with respect to paramagnetic centers under the influence of different types of Plasmodium. The correlation of two whole blood spectra in the initial phase of the P. falciparum and P. vivax infection provide an interesting comparison, see Fig. 6 and Table 6. The synchronous spectrum shows the dominant spectral features in the two compared EPR spectra [14]. Significant correlation relationships appear in the area of 1500–4000 Gs resonance fields, marked in Fig. 6A and B. The most intense auto-peak occurs at 3310 Gs (peroxyl radical) and at 2343 Gs (high-spin Fe3+ polynuclear aggregates, non-haem type proteins), while this is clearly weak in the low field range for 1656 Gs and 1545 Gs (both high-spin Fe3+, non-haem proteins). Peaks appearing outside the diagonal positions, the so-called cross-peaks, show a similar trend of changes between the two spectral intensities. Positive cross-peak appear for +(1699,3300) due to hs Fe3+, non-haem centres and peroxyl radicals. Negative cross-peaks −(2332,3304) and −(1544,3310) are derived from low-spin Fe3+, haem and high-spin Fe3+, non-haem centres and peroxyl radicals (Fig. 6C).

Fig. 6
figure 6

Synchronous (A) and asynchronous (B) 2T2D correlation EPR spectra of human whole blood infected with P. falciparum vs P. vivax in the magnetic field range of 5600–600 Gs; synchronous (C) and asynchronous (D) 2T2D correlation EPR spectra of human whole blood infected with P. falciparum vs P. vivax in the magnetic field range of 4000–1500 Gs

Table 6 The prominent 2T2D synchronous and asynchronous EPR correlation cross-peaks and their assignments for P. falciparum and P. vivax infected human whole blood, at 78 K, X-band (expressed as the size of the resonance fields [Gs] and the g-factors)

The 2T2D asynchronous spectrum contains cross-peaks located outside the diagonal positions (see Fig. 6B and Table 6). Two bands that correspond to the spectral coordinates of cross-peak, in the 2T2D asynchronous spectrum, come from vibrations of different moieties [14]. Two asynchronous peaks indicate that there are more copper centres in P. falciparum than the tyrosyl radicals(+(2.037, 2.002)) but fewer than the peroxyl radicals (−(2.069, 2.025)). The appearance of these cross-peaks indicate the importance of the multifunctional action of ceruloplasmin, affecting the changes taking place in the infected blood [72]. Several cross-peaks indicate ferric, high-spin signals, which clearly differ in the local symmetry of the surrounding proteins and characterize them. They are likely to define aggregated iron-storing, multinuclear species (+ (2.452, 2.030) with peroxyl radical, −(2.648, 1.995) with ls Fe3+, haem and −(3.068, 2.014) with peroxyl radical). These cross-peaks indicate that the spectral intensity contribution of ferric centers in the non-haem storage proteins of P. falciparum infected blood are observed in abundance. Regarding the P. falciparum infection, more low-spin iron haem centres appear than high-spin sites, associated with non-haem proteins (+(4.042, 1.995)), thereby indicating the virulence of this parasite. Another cross-peak (−(4.325, 2.002)) indicates that tyrosyl radicals are also generated in abundance in this infection. On the analysed map, the cross-peak (−(4.042, 2.446)) shows that more high-spin iron centres are observed in non-haem proteins related to iron transport, e.g., ferritin, than in iron accumulating proteins. The observed cross-peaks indicate that there is a specificity of the iron recycling rate in the blood for each type of parasite and identify which paramagnetic centers are important in this process.


Raman spectroscopy was used to monitor changes in the blood cells of patients diagnosed with malaria, who were treated in the University Hospital in Krakow, Poland. Statistical analysis showed no significant differences in standard laboratory tests between the two groups of patients diagnosed with P. falciparum or P. vivax.

The Raman spectra of red blood cells infected with Plasmodium, at the same time of hospitalization, were quite similar; it was difficult to identify the characteristics associated with a particular species of malaria parasite directly from the spectra.

The autopeak for wavenumber 1641 cm−1 observed on the 2D synchronous map for erythrocytes of patients diagnosed with P. falciparum malaria related to the formation of haemozoin is clearly shifted in relation to the position observed in the dynamic spectra (Table 3). This indicates the significant contribution to the 1641 cm−1 cross-peak of peptide bond vibrations from parasitic proteins in which numerous helical domains are present.

The most characteristic feature is the pattern of asynchronous 2D maps obtained for both types of Plasmodium, indicating a different dynamics of activity of both types of parasite, see Fig. 4C and D. An example of a difference in dynamics in the sequence of events is the opposite sign of the cross-peaks: positive +(1360,1642) for P. falciparum and negative −(1357,1642) for P. vivax. The first cross-peak listed for P. falciparum is generated by the ν4 deoxy-haem; Trp and Ala vibrations appears ahead of the ν10 and amide I (conf. α) vibrations. In this case of P. vivax, changes described by ν10 and amide I (conf. α) appear before those in ν4 and Trp. Plasmodium invasion proceeds through a series of complex stages of receptor-ligand interaction, a different pathway of vibrational energy flow, which is indicated by asynchronous cross-peaks. The observed dependencies show that these processes for each type of parasite have different time frames and are faster in the case of P. falciparum. Cross peaks from amino acids such as His, Trp, Tyr and Lys observed for P. falciparum indicate their participation in the formation of the PfRh5-basigin complex. In the case of P. vivax infection, asynchronous 2D cross peaks were demonstrated, in which νSS vibrations from Cys residues indicate the cysteine- rich protein PvRBP.

EPR spectra obtained at the beginning of the infection, analysed with the 2T2D method, indicate some differences in the iron recycling process, e.g., regarding its storage in proteins. In blood infected with P. falciparum, correlation peaks manifest the presence of numerous iron centers characterizing non-haem blood storage proteins. More low-spin iron haem centres associated with non-haem proteins are observed for P. falciparum infection, indicating the virulence of this parasite.

To our knowledge, this is the first observation in which Plasmodium spp. were discriminated using the 2D-COS method to analyse their activity through their influence on the erythrocytes of hospitalized patients, through the use of Raman and EPR spectroscopy. This analysis is intended to contribute to greater understanding of the phenomena occurring in red blood cells during infection with various types of Plasmodium.

Availability of data and materials

All data generated or analyzed during this study are included in this published article. The datasets analyzed during the current study are available from the corresponding author on reasonable request. Samples are not available.


  1. WHO. World malaria report 2021. Geneva: World Health Organization; 2021.

    Google Scholar 

  2. Czarkowski MP, Staszewska-Jakubik E, Wielgosz U. Infectious diseases and poisonings in Polandin 2020. Warszawa: National Institute of Public Health; 2021.

    Google Scholar 

  3. Baird JK. Evidence and implications of mortality associated with acute Plasmodium vivax malaria. Clin Microbiol Rev. 2013;26:36–57.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Martín-Jaular L, Elizalde-Torrent A, Thomson-Luque R, Ferrer M, Segovia JC, Herreros-Aviles E, et al. Reticulocyte-prone malaria parasites predominantly invade CD71hi immature cells: implications for the development of an in vitro culture for Plasmodium vivax. Malar J. 2013;12:434.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Galinski MR, Meyer EVS, Barnwell JW. Plasmodium vivax: modern strategies to study a persistent parasite’s life cycle. Adv Parasitol. 2013;81:1–26.

    Article  PubMed  Google Scholar 

  6. Cowman AF, Healer J, Marapana D, Marsh K. Malaria: biology and disease. Cell. 2016;167:610–24.

    Article  CAS  PubMed  Google Scholar 

  7. Baird JK. Management of Plasmodium vivax risk and illness in travelers. Trop Dis Travel Med Vaccines. 2017;3:7.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Birczyńska-Zych M, Czepiel J, Łabanowska M, Kraińska M, Biesiada G, Moskal P, et al. Could Raman spectroscopy distinguish between P. falciparum and P. vivax infection? Clin Spectrosc. 2021;3:100015.

    Article  Google Scholar 

  9. Wesełucha-Birczyńska A, Kozicki M, Czepiel J, Łabanowska M, Nowak P, Kowalczyk G, et al. Human erythrocytes analyzed by generalized 2D Raman correlation spectroscopy. J Mol Struct. 2014;1069:305–12.

    Article  Google Scholar 

  10. Birczyńska-Zych M, Czepiel J, Łabanowska M, Kurdziel M, Biesiada G, Kozicki M, et al. The aging of P. falciparum infected RBCs by 2D-correlation Raman and EPR spectroscopy. J Mol Struct. 2021;1224:129036.

    Article  Google Scholar 

  11. Wesełucha-Birczyńska A, Zięba-Palus J. Analysis of biological samples using vibrational spectroscopy methods. In: Buszewski B, Baranowska I, editors. Handbook of bioanalytics. Cham: Springer Nature; 2022. p. 333–52.

    Chapter  Google Scholar 

  12. Noda I, Dowrey AE, Marcott C, Story GM, Ozaki Y. Generalized two-dimensional correlation spectroscopy. Appl Spectrosc. 2000;54:236A-248A.

    Article  CAS  Google Scholar 

  13. Noda I, Ozaki Y. Two-dimensional correlation spectroscopy. Applications in vibrational and optical spectroscopy. Chichester: Wiley; 2004.

    Book  Google Scholar 

  14. Noda I. Two-trace two-dimensional (2T2D) correlation spectroscopy—a method for extracting useful information from a pair of spectra. J Mol Struct. 2018;1160:471–8.

    Article  CAS  Google Scholar 

  15. Wood BR, McNaughton D. Raman excitation wavelength investigation of single red blood cells in vivo. J Raman Spectrosc. 2002;33:517–23.

    Article  CAS  Google Scholar 

  16. Moxon CA, Grau E, Craig AG. Malaria: modification of the red blood cell and consequences in the human host. Br J Haematol. 2011;154:670–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Chen L, Deng H, Cui H, Fang J, Zuo Z, Deng J, Li Y, Wang X, Zhao L. Inflammatory responses and inflammation-associated diseases in organs. Oncotarget. 2018;9:7204–18.

    Article  PubMed  Google Scholar 

  18. Wesełucha-Birczyńska A, Kozicki M, Czepiel J, Birczyńska M. Raman micro-spectroscopy tracing human lymphocyte activation. Analyst. 2013;138:7157–63.

    Article  PubMed  Google Scholar 

  19. Cowman AF, Tonkin CJ, Tham W-H, Duraisingh MT. The molecular basis of erythrocyte invasion by malaria parasites. Cell Host Microbe. 2017;22:232–45.

    Article  CAS  PubMed  Google Scholar 

  20. Spiker RC Jr, Levin IW. Effect of bilayer curvature on vibrational Raman spectroscopic behavior of phospholipid-water assemblies. Biochim Biophys Biomembr. 1976;455:560–75.

    Article  CAS  Google Scholar 

  21. Deitsch KW, Wellems TE. Membrane modifications in erythrocytes parasitized by Plasmodium falciparum. Mol Biochem Parasitol. 1996;76:1–10.

    Article  CAS  PubMed  Google Scholar 

  22. McNaughton D, Wood BR. Resonance Raman spectroscopy in malaria research. Expert Rev Proteom. 2006;3:525–44.

    Article  Google Scholar 

  23. Tu AT. Raman spectroscopy in biology: principles and applications. New York: Wiley; 1982.

    Google Scholar 

  24. Hviid L, Jensen ATR. A parasite protein family of key importance in Plasmodium falciparum malaria immunity and pathogenesis. Adv Parasitol. 2015;88:51–84.

    Article  PubMed  Google Scholar 

  25. Montemiglio LC, Testi C, Ceci P, Falvo E, Pitea M, Savino C, et al. Cryo-EM structure of the human ferritin–transferrin receptor 1 complex. Nat Commun. 2019;10:1121.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Galinski MR, Corredor Medina C, Ingravallo P, Barnwell JW. A reticulocyte-binding protein complex of Plasmodium vivax merozoites. Cell. 1992;69:1213–26.

    Article  CAS  PubMed  Google Scholar 

  27. Lagant P, Vergoten G, Loucheux C, Fleury G. Study of Poly(L-aspartic acid). I. Laser Raman spectrometry. Polym J. 1979;11:345–51.

    Article  CAS  Google Scholar 

  28. Takeuchi H. Raman structural markers of tryptophan and histidine side chains in proteins. Biopolymers (Biospectroscopy). 2003;72:305–17.

    Article  CAS  PubMed  Google Scholar 

  29. Maruyama T, Takeuchi H. Effects of hydrogen bonding and side-chain conformation on the Raman bands of tryptophan-2,4,5,6,7-d. J Raman Spectrosc. 1995;26:319–24.

    Article  CAS  Google Scholar 

  30. Hsiao LL, Howard RJ, Aikawa T, Taraschi F. Modification of host cell membrane lipid composition by the intra-erythrocytic human malaria parasite Plasmodium falciparum. Biochem J. 1991;274:121–32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Knapp B, Hundt E, Lingelbach KR. Structure and possible function of Plasmodium falciparum proteins exported to the erythrocyte membrane. Parasitol Res. 1991;77:277–82.

    Article  CAS  PubMed  Google Scholar 

  32. Papalexis V, Siomos MA, Campanale N, Guo X, Kocak G, Foley M, et al. Histidine-rich protein 2 of the malaria parasite, Plasmodium falciparum, is involved in detoxification of the by-products of haemoglobin degradation. Mol Biochem Parasitol. 2001;115:77–86.

    Article  CAS  PubMed  Google Scholar 

  33. Garfinkel D, Edsall JT. Raman spectra of amino acids and related compounds. XI. The ionization of cysteine. J Am Chem Soc. 1958;80:3823–6.

    Article  CAS  Google Scholar 

  34. Silva BL, Freire PTC, Melo FEA, Guedes I, Araujo Silva MA, Mendes Filho J, et al. Polarized Raman spectra and infrared analysis of vibrational modes in L-threonine crystals. Braz J Phys. 1998;28:19–24.

    Article  CAS  Google Scholar 

  35. Takeuchi H, Watanabe N, Satoh Y, Harada I. Effects of hydrogen bonding on the tyrosine Raman bands in the 1300–1150 cm-1 region. J Raman Spectrosc. 1989;20:233–7.

    Article  CAS  Google Scholar 

  36. De Gelder J, De Gussem K, Vandenabeele P, Moens L. Reference database of Raman spectra of biological molecules. J Raman Spectrosc. 2007;38:1133–47.

    Article  Google Scholar 

  37. Garfinkel D. Raman spectra of amino acids and related compounds. XII. Various amino acids derived from proteins and creatine. J Am Chem Soc. 1958;80:3827–31.

    Article  CAS  Google Scholar 

  38. Li J, Han E-T. Dissection of the Plasmodium vivax reticulocyte binding-like proteins (PvRBPs). Biochem Biophys Res Commun. 2012;426:1–6.

    Article  CAS  PubMed  Google Scholar 

  39. Kanjee U, Rangel GW, Clark MA, Duraisingh MT. Molecular and cellular interactions defining the tropism of Plasmodium vivax for reticulocytes. Curr Opin Microbiol. 2018;46:109–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Marti M, Baum J, Rug M, Tilley L, Cowman AF. Signal-mediated export of proteins from the malaria parasite to the host erythrocyte. J Cell Biol. 2005;171:587–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Misra NK, Kapoor D, Tandon P, Gupta VD. Vibrational dynamics and heat capacity of poly(L-lysine). Polym J. 1997;29:914–22.

    Article  CAS  Google Scholar 

  42. Patarroyo MA, Molina-Franky J, Gómez M, Arévalo-Pinzón G, Patarroyo ME. Hotspots in Plasmodium and RBC receptor-ligand interactions: key pieces for inhibiting malarial parasite invasion. Int J Mol Sci. 2020;21(13):4729.

  43. Gluzman Y, Francis SE, Oksman A, Smith CE, Duffin KL, Goldberg DE, Order and Specificity of the Plasmodium falciparum Hemoglobin Degradation Pathway J Clin Invest. 1994;93:1602–08.

  44. Wright KE, Hjerrild KA, Bartlett J, Douglas AD, Jin J, Brown RE, et al. Structure of malaria invasion protein RH5 with erythrocyte basigin and blocking antibodies. Nature. 2014;515:427–30.

  45. Gruszczyk J, Huang RK, Chan LJ, Menant S, Hong C, Murphy JM, et al. Cryo-EM structure of an essential Plasmodium vivax invasion complex. Nature. 2018;559:135–9.

    Article  CAS  PubMed  Google Scholar 

  46. Cowman AF, Crabb BS. Invasion of red blood cells by malaria parasites. Cell. 2006;124:755–66.

    Article  CAS  PubMed  Google Scholar 

  47. Yamashita S, Mizuno M, Tran DP, Dokainish H, Kitao A, Mizutani Y. Vibrational energy transfer from heme through atomic contacts in proteins. J Phys Chem B. 2018;122:5877–84.

    Article  CAS  PubMed  Google Scholar 

  48. Muramatsu T. Basigin (CD147), a multifunctional transmembrane glycoprotein with various binding partners. J Biochem. 2016;159:481–90.

    Article  CAS  PubMed  Google Scholar 

  49. Crosnier C, Bustamante LY, Bartholdson SJ, Bei AK, Theron M, Uchikawa M, Mboup S, Ndir O, Kwiatkowski DP, Duraisingh MT, Rayner JC, Wright GJ. BASIGIN is a receptor essential for erythrocyte invasion by Plasmodium falciparum. Nature. 2012;480:534–7.

    Article  CAS  Google Scholar 

  50. Rathore S, Dass S, Kandari D, Kaur I, Gupta M, Sharma YD. Basigin interacts with Plasmodium vivax tryptophan-rich antigen PvTRAg38 as a second erythrocyte receptor to promote parasite growth. J Biol Chem. 2017;292:462–76.

    Article  CAS  PubMed  Google Scholar 

  51. Baker HM, Mason AB, He QY, Mac Gillivray RTA, Baker EN. Ligand variation in the transferrin family: the crystal structure of the H249Q mutant of the human transferrin N-lobe as a model for iron binding in insect transferrins. Biochemistry. 2001;40:11670–5.

    Article  CAS  PubMed  Google Scholar 

  52. Tran PN, Brown SHJ, Rug M, Ridgway MC, Mitchell TW, Maier AG. Changes in lipid composition during sexual development of the malaria parasite Plasmodium falciparum. Malar J. 2016;15:73.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Krzyminiewski R, Kruczynski Z, Dobosz B, Zajac A, Mackiewicz A, Leporowska E, et al. EPR study of iron ion complexes in human blood. Appl Magn Reson. 2011;40:321–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Kubiak T, Krzyminiewski R, Dobosz B. EPR study of paramagnetic centers in human blood. Curr Top Biophys. 2013;36:7–13.

    Article  Google Scholar 

  55. Peisach J, Blumberg WE, Ogawa S, Rachmilewitz EA, Oltzik R. The effects of protein conformation on the heme symmetry in high spin ferric heme proteins as studied by electron paramagnetic resonance. J Biol Chem. 1971;246:3342–55.

    Article  CAS  PubMed  Google Scholar 

  56. Blumberg WE, Peisach J. Low-spin compounds of heme proteins. In: Blumberg WE, editor. Advances in Chemistry, chapter 13. Washington: American Chemical Society; 1971.

    Google Scholar 

  57. Peisach J, Blumberg WE, Wittenberg BA, Wittenberg JB, Kampa L. On the state of the iron and the nature of the ligand in oxyhemoglobin. Proc Natl Acad Sci USA. 1969;63:934–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Azarkh M, Gast P, Mason AB, Groenen EJJ, Mathies G. Analysis of the EPR spectra of transferrin: the importance of a zero-field-splitting distribution and 4th-order terms. Phys Chem Chem Phys. 2019;21:16937–48.

    Article  CAS  PubMed  Google Scholar 

  59. Walker FA. Magnetic spectroscopic (EPR, ESEEM, Mossbauer, MCD and NMR) studies of low-spin ferriheme centers and their corresponding heme proteins. Coord Chem Rev. 1999;185–186:471–534.

    Article  Google Scholar 

  60. Aime S, Bergamasco B, Biglino D, Digilio G, Fasano M, Giamello E, et al. EPR investigations of the iron domain in neuromelanin. Biochim Biophys Acta. 1997;1361:49–58.

    Article  CAS  PubMed  Google Scholar 

  61. Svistunenko DA, Sharpe MA, Nicholls P, Blenkinsop C, Davies NA, Dunne J, et al. The pH dependence of naturally occurring low-spin forms of methaemoglobin and metmyoglobin: an EPR study. Biochem J. 2000;351:595–605.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Rylkov VV, Tarasiev MYu, Moshkov KA. Labile conformation of type 2 Cu2+ centres in human ceruloplasmin. Eur J Biochem. 1991;197:185–9.

    Article  CAS  PubMed  Google Scholar 

  63. Svistunenko DA, Davies NA, Wilson MT, Stidwill RP, Singer M, Cooper CE. Free radical in blood: a measure of haemoglobin autoxidation in vivo? J Chem Soc Perkin Trans. 1997;2:2539–43.

    Article  Google Scholar 

  64. Kehrer JP. The Haber–Weiss reaction and mechanisms of toxicity. Toxicology. 2000;149:43–50.

    Article  CAS  PubMed  Google Scholar 

  65. Chamulitrat W, Mason RP. Lipid peroxyl radical intermediates in the peroxidation of polyunsaturated fatty acids by lipoxygenase. J Biol Chem. 1989;264:20968–73.

    Article  CAS  PubMed  Google Scholar 

  66. Svistunenko DA. An EPR study of the peroxyl radicals induced by hydrogen peroxide in the haem proteins. Biochim Biophys Acta. 2001;1546:365–78.

    Article  CAS  PubMed  Google Scholar 

  67. Un S, Gerez C, Elleingand E, Fontecave M. Sensitivity of tyrosyl radical g-values to changes in protein structure: a high-field EPR study of mutants of ribonucleotide reductase. J Am Chem Soc. 2001;123:3048–54.

    Article  CAS  PubMed  Google Scholar 

  68. Svistunenko DA, Dunne J, Fryer M, Nicholls P, Reeder BJ, Wilson MT, et al. Comparative study of tyrosine radicals in hemoglobin and myoglobins treated with hydrogen peroxide. Biophys J. 2022;83:2845–55.

    Article  Google Scholar 

  69. Svistunenko DA, Cooper CE. A new method of identifying the site of tyrosyl radicals in proteins. Biophys J. 2004;87:582–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Pisciotta JM, Sullivan D. Hemozoin: oil versus water. Parasitol Int. 2008;57:89–96.

    Article  CAS  PubMed  Google Scholar 

  71. Atamna H, Ginsburg H. Origin of reactive oxygen species in erythrocytes infected with Plasmodium falciparum. Mol Biochem Parasitol. 1993;61:231–41.

    Article  CAS  PubMed  Google Scholar 

  72. Gutteridge JMC. Caeruloplasmin: a plasma protein, enzyme, and antioxidant. Ann Clin Biochem. 1978;15:293–6.

    Article  CAS  PubMed  Google Scholar 

Download references


MB-Z acknowledge the support of InterDokMed project no. POWR.03.02.00-00-I013/16. This study was supported by the research part of the subsidy from the Faculty of Chemistry of the Jagiellonian University in Krakow, Poland.


MB-Z acknowledge the financial support of InterDokMed project no. POWR.03.02.00-00-I013/16.

Author information

Authors and Affiliations



MBZ: methodology, investigation: visualization: writing—original draft. JC: methodology, data curation, writing—review and editing. MŁ—methodology, formal analysis, writing—review and editing. MarK, MagK: methodology, investigation. GB, AG: writing—review and editing. AWB: conceptualization, formal analysis, visualization: writing—review and editing. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Aleksandra Wesełucha-Birczyńska.

Ethics declarations

Ethics approval and consent to participate

The research was conducted in accordance with the guidelines for good clinical practice (GCP) according to the Ethical Principles for Medical Research Involving Human Subjects (the Declaration of Helsinki). The study was approved by the Bioethics Committee of the Jagiellonian University (reference No KBET/275/B/2011).

Consent for publication

The authors declare consent for publication.

Competing interests

The authors declare no competing of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Birczyńska-Zych, M., Czepiel, J., Łabanowska, M. et al. Course of Plasmodium infection studied using 2D-COS on human erythrocytes. Malar J 22, 188 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: