FTIR optimisation for urine-based samples

FTIR interrogation of urine samples was carried out in order to optimise methodology; it was important to consider the subsequent clinical use of this FTIR methodology with focus on the volumes of samples obtained (Lovergne et al., 2015). Human samples are costly, have specific storage and handling requirements and are available in limited amounts, therefore rat urine was used as alternative to human samples for optimisation experiment work (Chapter 3); this enabled testing of urine volumes needed to produce reproducible spectra from as low volumes as possible.

Previous research has indicated differences in both protein bands (main amide bands have focussed on the region (1700-1550 cm-1) and lipid regions (~3100-2700 cm-1) (Raouf et al., 2011). Since the thesis hypothesis was focussed on protein/ peptide biomarkers being found in urine from patients with PE and IUGR, the amide region was used for optimisation of signal clarity. A bands of amide I, II at range (1800-1500 cm-1) were assessed by peak area, height peak, and wavenumber of peak maximum to understand

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both the noise levels in terms of absorbance intensity and band reproducibility of band position, (Figure. 3.7 and 3.8). Spectra obtained from urine samples clearly showed amide bands with good sample repeat consistency. Peak height showed some degree of variance (Figure 3.8) having a mean of 0.175 with standard error of 0.053, which was most reliable with volumes of 5 μL. As this is a measure of in essence a single point within the spectra the level of noise can be expected. For this reason, the area (integrating under the amide profile) was used; this takes into account any variance across the whole region of interest and so ~ 60 data points were assessed rather than just 1 at the maximum. This is a common route used for the comparison of such spectra (Lovergne et al., 2015). In addition to this, optimisation of data processing showed the reduced signal / noise, but importantly maintained consistency of data, when spectral smoothing was applied. There are always concerns that use of smoothing algorithms introduces spectral artefacts (Mukherjee et al., 2014), and for this reason a low level 5 point adjacent averaging smoothing function was applied (Baker et al., 2010).

Using amide I as the main band upon which methods were optimised, this work demonstrated a very good signal to noise ratio across the whole mid-IR range from samples with volumes as low as 5 μL. Figure (3.8) showed variability of observed signal according to volumes of 1, 2, 5 and 10 μL. However, results indicate a higher sensitivity related to most parameters at 5 and 10 μL vs 1 and 2 μL Figure (3.8). Previous research by (Hoşafçı et al., 2007) used 5 μL of sample to investigate FTIR spectral vibration of urine and blood samples, other studies also used this volume of biofluid typically blood sample for FTIR analysis (Bonnier et al., 2014, Lovergne et al., 2015). Bonnier and co-workers (2014) revealed good improvement in FTIR spectra identification after protein fractions

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using centrifugal filtrate at different molecular weight cut-off using blood sample at 5 μL, especially after centrifugal filtrate purification prior sampling. This was a very positive outcome since the total volumes expected from human samples (after processing; protein fractionation, etc.) and protein fractionation to establish the lowest reliable volumes which could be used to assess clinical samples, and which would be the best method to possibly identify spectral differences. A simple ultrafiltration protocol, based on molecular weight fractionation was used, enabling spectral profile determination of samples with improved observation of amide band (Bonnier et al., 2014)

The outcome of optimisation of FTIR sampling demonstrated lower limits of reliable FTIR sampling. The second optimisation experiment was carried out to determine the influence of sample preparation procedure on FTIR spectra at different conditions including (whole rat urine, >10 kDa ultrafiltration urine sample without buffer exchange and >10 kDa after sample buffer exchange). (Bonnier et al., 2014) has used ultrafiltration fractions bases on molecular weight cut-off to improve spectral profile outcome of blood sample. However, centrifugal filtrate bases on molecular weight cut-off coupled with buffer exchange method (Hart et al., 2015, Çorbacı and Uçar, 2018) enabling to introduce a simple and robust methodology by removing unwanted molecules (Hall, 2015) that has a similar functional group and could be overlapping with the sample of interest. Ultrafiltration experiments displayed spectra peaks visibly of retentate of > 10 kDa compare with spectra of whole urine sample (Figure 3.9). Protein bands are clearly observed after retentate buffer exchange (see Figure.3.9 C) at spectra range 1700-1650 cm-1 with distinct peak at ~1650 cm-1 (amide I). A band of amide II observed at 1650-1500 cm-1, amide III peak at ~1330-1220 cm-1 was also observed (Lacombe et al., 2015).

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Similarly, the spectra correspond to amide A and OH bands at 3650-3500 cm-1 and also C- H stretching band at 3000-2830 cm-1 in IR (Lacombe et al., 2015). Although no attempt has been made to quantify the spectral characteristics corresponds to the constituent components in the urine, the study rather demonstrates that using such centrifugal fractionation procedure there is a passivity for ultimately developing medical diagnostics using this methodology.

In Chapter 4 the SOP that was established in Chapter 3 for urine sample analysis was applied to clinical samples. This strategy was used to investigate spectral profile of clinical samples in different pregnancy time points using FTIR technique. The first aim was to investigate spectral profile of PE related to case and control during both 15 and 20 weeks of gestational age respectively. The second aim was to investigate spectral profile of IUGR related to case and control during both 15 and 20 weeks of pregnancy respectively.