Understanding mobile phase buffer composition and chemical structure effects on electrospray ionization mass spectrometry response.

Mobile phase selection is of critical importance in liquid chromatography - mass spectrometry (LC-MS) based studies, since it affects retention, chromatographic selectivity, ionization, limits of detection and quantification, and linear dynamic range. Generalized LC-MS mobile phase selection criteria, suitable for a broad class of chemical compounds, do not exist thus far. Here we have performed a large-scale qualitative assessment of the effect of solvent composition used for reversed-phase LC separations on electrospray ionization (ESI) response for 240 small molecular weight drugs, representing various chemical compound classes. Of these 240 analytes 224 were detectable using ESI. The main chemical structural features affecting ESI response were found to all be surface area or surface charge-related. Mobile phase composition was found to be less differentiating, although for some compounds a pH effect was noted. Unsurprisingly, chemical structure was found to be the dominant factor for ESI response for the majority of the investigated analytes, representing about 85% of the replicating detectable complement of the sample data set. A weak correlation between ESI response and structure complexity was observed. Solvents based on isopropanol, and those containing phosphoric or di- and trifluoracetic acids, performed relatively poorly in terms of chromatographic or ESI response, whilst the best performing 'generic' LC solvents were based on methanol, acetonitrile using formic acid and ammonium acetate as buffer components, consistent with current practice in many laboratories.

Rapid and sensitive detection of SARS-CoV-2 infection using quantitative peptide enrichment LC-MS analysis.

Reliable, robust, large-scale molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for monitoring the ongoing coronavirus disease 2019 (COVID-19) pandemic. We have developed a scalable analytical approach to detect viral proteins based on peptide immuno-affinity enrichment combined with liquid chromatography-mass spectrometry (LC-MS). This is a multiplexed strategy, based on targeted proteomics analysis and read-out by LC-MS, capable of precisely quantifying and confirming the presence of SARS-CoV-2 in phosphate-buffered saline (PBS) swab media from combined throat/nasopharynx/saliva samples. The results reveal that the levels of SARS-CoV-2 measured by LC-MS correlate well with their correspondingreal-time polymerase chain reaction (RT-PCR) read-out (r = 0.79). The analytical workflow shows similar turnaround times as regular RT-PCR instrumentation with a quantitative read-out of viral proteins corresponding to cycle thresholds (Ct) equivalents ranging from 21 to 34. Using RT-PCR as a reference, we demonstrate that the LC-MS-based method has 100% negative percent agreement (estimated specificity) and 95% positive percent agreement (estimated sensitivity) when analyzing clinical samples collected from asymptomatic individuals with a Ct within the limit of detection of the mass spectrometer (Ct ≤ 30). These results suggest that a scalable analytical method based on LC-MS has a place in future pandemic preparedness centers to complement current virus detection technologies.

Profiling of the known-unknown Passiflora variant complement by liquid chromatography - Ion mobility - Mass spectrometry.

Liquid Chromatography - Ion Mobility - Mass Spectrometry (LC-IM-MS) was utilized for non-targeted screening analysis to understand the variance in the composition of Passiflora species. Multivariate analysis was employed to explore a chemometric processing strategy for IM based Passiflora variant differentation. This approach was applied to the comparative analyses of extracts of the medicinal plants Passiflora alata, Passiflora edulis, Passiflora incarnata and Passiflora caerulea. In total, 255 occurrences of IM-MS resolved coeluting marker isomers and isobaric species were detected, providing increased coverage and specificity of species component markers compared to conventional LC-MS. A large proportion of medical plant phytochemical analysis information often remains redundant in that it is not phenotypic specific. Here, generation of Passiflora variant 'known-unknown' libraries has been used to compare Passiflora species to investigate unique variant features. Investigations of predicted collision cross section have enabled comparison of an element of the 'known-unknown' IM isomeric complement to be performed, facilitating a reduction in the number of possible variant unique isomeric identifications. In combination with spectral interpretation, it has been possible to resassign isomeric 'known-unknowns' as 'knowns'. The strategies employed illustrates the potential to facilitate identification of medicinal plant phytochemical components.

Excessive dietary lipid intake provokes an acquired form of lysosomal lipid storage disease in the kidney.

Obesity and dyslipidaemia are features of the metabolic syndrome and risk factors for chronic kidney disease. The cellular mechanisms connecting metabolic syndrome with chronic kidney disease onset and progression remain largely unclear. We show that proximal tubular epithelium is a target site for lipid deposition upon overnutrition with a cholesterol-rich Western-type diet. Affected proximal tubule epithelial cells displayed giant vacuoles of lysosomal or autophagosomal origin, harbouring oxidised lipoproteins and concentric membrane layer structures (multilamellar bodies), reminiscent of lysosomal storage diseases. Additionally, lipidomic analysis revealed renal deposition of cholesterol and phospholipids, including lysosomal phospholipids. Proteomic profiles of renal multilamellar bodies were distinct from those of epidermis or lung multilamellar bodies and of cytoplasmic lipid droplets. Tubular multilamellar bodies were observed in kidney biopsies of obese hypercholesterolaemic patients, and the concentration of the phospholipidosis marker di-docosahexaenoyl (22:6)-bis(monoacylglycerol) phosphate was doubled in urine from individuals with metabolic syndrome and chronic kidney disease. The enrichment of proximal tubule epithelial cells with phospholipids and multilamellar bodies was accompanied by enhanced inflammation, fibrosis, tubular damage markers, and higher urinary electrolyte content. Concomitantly to the intralysosomal lipid storage, a renal transcriptional response was initiated to enhance lysosomal degradation and lipid synthesis. In cultured proximal tubule epithelial cells, inhibition of cholesterol efflux transport or oxysterol treatment induced effects very similar to the in vivo situation, such as multilamellar body and phospholipid amassing, and induction of damage, inflammatory, fibrotic, and lipogenic molecules. The onset of phospholipidosis in proximal tubule epithelial cells is a novel pathological trait in metabolic syndrome-related chronic kidney disease, and emphasises the importance of healthy lysosomes and nutrition for kidney well-being. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Biomarkers for lysosomal storage disorders: identification and application as exemplified by chitotriosidase in Gaucher disease.

UNLABELLED: A biomarker is an analyte that indicates the presence of a biological process linked to the clinical manifestations and outcome of a particular disease. An ideal biomarker provides indirect but ongoing determinations of disease activity. In the case of lysosomal storage disorders (LSDs), metabolites or proteins specifically secreted by storage cells are good candidates for biomarkers. Potential clinical applications of biomarkers are found in improved diagnosis, monitoring of disease progression and assessment of therapeutic correction. These applications are illustrated by reviewing the use of plasma chitotriosidase in the clinical management of patients with Gaucher disease, the most common LSD. The ongoing debate on the value of biomarkers in patient management is addressed. Novel analytical methods have revolutionized the identification and measurement of biomarkers at the protein and metabolite level. Recent developments in biomarker discovery by proteomics are described and the future for biomarkers of LSDs is discussed. CONCLUSION: Besides direct applications for biomarkers in patient management, biomarker searches are likely to render new insights into pathophysiological mechanisms and metabolic adaptations, and may provide new targets for therapeutic intervention.