Metabolic fingerprinting of high-fat plasma samples processed by centrifugation- and filtration-based protein precipitation delineates significant differences in metabolite information coverage

Metabolomics and metabolic fingerprinting are being extensively employed for improved understanding of biological changes induced by endogenous or exogenous factors. Blood serum or plasma samples are often employed for metabolomics studies. Plasma protein precipitation (PPP) is currently performed in most laboratories before LC–MS analysis. However, the impact of fat content in plasma samples on metabolite coverage has not previously been investigated. Here, we have studied whether PPP procedures influence coverage of plasma metabolites from high-fat plasma samples. An optimized UPLC-QTOF/MS metabolic fingerprinting approach and multivariate modeling (PCA and OPLS-DA) were utilized for finding characteristic metabolite changes induced by two PPP procedures; centrifugation and filtration. We used 12-h fasting samples and postprandial samples collected at 2 h after a standardized high-fat protein-rich meal in obese non-diabetic subjects recruited in a dietary intervention. The two PPP procedures as well as external and internal standards (ISs) were used to track errors in response normalization and quantification. Remarkably and sometimes uniquely, the fPPP, but not the cPPP approach, recovered not only high molecular weight (HMW) lipophilic metabolites, but also small molecular weight (SMW) relatively polar metabolites. Characteristic SMW markers of postprandial samples were aromatic and branched-chain amino acids that were elevated (p < 0.001) as a consequence of the protein challenge. In contrast, some HMW lipophilic species, e.g. acylcarnitines, were moderately lower (p < 0.001) in postprandial samples. LysoPCs were largely unaffected. In conclusion, the fPPP procedure is recommended for processing high-fat plasma samples in metabolomics studies. While method improvements presented here were clear, use of several ISs revealed substantial challenges to untargeted metabolomics due to large and variable matrix effects.     

A biospectroscopic interrogation of fine needle aspirates points towards segregation between graded categories: an initial study towards diagnostic screening

Fine needle aspirates (FNAs) of suspicious breast lesions are often used to aid the diagnosis of female breast cancer. Biospectroscopy tools facilitate the acquisition of a biochemical cell fingerprint representative of chemical bonds present in a biological sample. The mid-infrared (IR; 4,000–400 cm⁻¹) is absorbed by the chemical bonds present, allowing one to derive an absorbance spectrum. Complementary to IR spectroscopy, Raman spectroscopy measures the scattering by chemical bonds following excitation by a laser to generate an intensity spectrum. Our objective was to apply these methods to determine whether a biospectroscopy approach could objectively segregate different categories of FNAs. FNAs of breast tissue were collected (n = 48) in a preservative solution and graded into categories by a cytologist as C1 (non-diagnostic), C2 (benign), C3 (suspicious, probably benign) or C5 (malignant) [or C4 (suspicious, probably malignant); no samples falling within this category were identified during the collection period of the study]. Following washing, the cellular material was transferred onto BaF₂ (IR-transparent) slides for interrogation by Raman or Fourier-transform IR (FTIR) microspectroscopy. In some cases where sufficient material was obtained, this was transferred to low-E (IR-reflective) glass slides for attenuated total reflection–FTIR spectroscopy. The spectral datasets produced from these techniques required multivariate analysis for data handling. Principal component analysis followed by linear discriminant analysis was performed independently on each of the spectral datasets for only C2, C3 and C5. The resulting scores plots revealed a marked overlap of C2 with C3 and C5, although the latter pair were both significantly segregated (P < 0.001) in the Raman spectra. Good separation was observed between C3 and C5 in all three spectral datasets. Analysis performed on the average spectra showed the presence of three distinct cytological groups. Our findings suggest that biospectroscopy tools coupled with multivariate analysis may support the current FNA tests whilst increasing the sensitivity and associated reliability for improved diagnostics.     

1,1′‐Di(hydrazinocarbonylmethyl)‐2,2′‐biimidazole monohydrate and 1,1′‐di[2‐(hydrazinocarbonyl)ethyl]‐2,2′‐bi­imidazole

The crystal structures of the title compounds, alternatively called 2,2′‐(2,2′‐bi­imid­azole‐1,1′‐diyl)­diaceto­hydra­zide monohydrate, C₁₀H₁₄N₈O₂·H₂O, (I), and 3,3′‐(2,2′‐bi­imid­azole‐1,1′‐diyl)­dipropion­o­hydra­zide, C₁₂H₁₈N₈O₂, (II), respectively, have been determined. The mol­ecules consist of half‐mol­ecule asymmetric units related by a twofold rotation in (I) and by a center of inversion in (II). The imidazole rings of both mol­ecules crystallize in a nearly coplanar fashion [dihedral angles of 5.91 (3) and 0.0 (1)° for (I) and (II), respectively]. Both planar hy­dra­zinocarbonylalkyl substituents are essentially planar and assume the E orientation.     

Comment to T. Chen Letter to the Editor,Transport in Porous Media 41, 241–243, 2000

Transport in Porous Media -