Biology subjects

Naicker, P.

Publications and source records attributed to Naicker, P..

6 recordsLinked to original sources

bioRxiv2025

Arachidonic acid modulates fluconazole-induced responses in Candida albicans biofilms

Candida albicans is a human commensal, which causes opportunistic infections with high morbidity and mortality and is characterised by the production of resistant biofilms. Polyunsaturated fatty acids, such as arachidonic acid, can increase azole susceptibility of C. albicans biofilms significantly. However, the underlining mechanism is not known. We investigated the effect of arachidonic acid on known fluconazole resistance mechanisms namely, overexpression of ERG11, increased ergosterol content, oxidative stress resistance, as well as expression and activity of the efflux pump, Cdr1p. Upregulation of ERG11 was observed in biofilms exposed to fluconazole. However, this was reversed in the presence of arachidonic acid, even in the presence of fluconazole. Furthermore, arachidonic acid downregulated the fluconazole-induced oxidative stress response of C. albicans. Previous transcriptome data indicated a significant increase in CDR1 expression during early biofilm formation in the presence of arachidonic acid. However, we found that efflux activity was reduced in the presence of arachidonic acid, which indicates the loss of function of the membrane-associated protein. This contradictory phenomenon was further investigated by determining the effect of arachidonic acid on the localisation and phosphorylation of Cdr1p (ProteomeXchange identifier PXD070958). Our results show that the presence of arachidonic acid may cause mislocalisation and changes in the phosphorylation of Cdr1p; all of which could impact its activity. These results demonstrate that multiple mechanisms are potentially involved in the arachidonic acid-induced increased fluconazole susceptibility and allows for further exploration of lipid-mediated modulation of antifungal responses.

microbiology↗

bioRxiv2024

Plasma proteome profiling for AKI biomarker candidates associated with first-line ART in people living with HIV in South Africa

With the highest global burden of HIV, South Africa initiates HIV treatment using first-line antiretroviral therapy (ART) regimens in newly diagnosed patients. Antiretroviral (ARV)-associated nephrotoxicity has been observed in -10% of South African patients newly receiving first-line ART, as well as in patients who have extensively received TDF-based ART regimens, and this can progress to acute kidney injury (AKI). To identify potential biomarkers that will improve the detection of ARV-associated nephrotoxicity, proteomic analysis was performed using the sequential window acquisition of all theoretical mass spectra (SWATH-MS) data acquisition method on the plasma of the case group (AKI) and the control group (non-AKI). Data are available via ProteomeXchange with identifier PXD054218. Evaluation of the results identified thirty-four proteins that showed a significant change in abundance, with three proteins showing increased abundance, while thirty-one proteins showed decreased abundance between the AKI and non-AKI groups. Machine learning was also used to evaluate the results and showed twenty ranked proteins that contributed to distinguishing between the AKI and non-AKI groups. The majority of the proteins of significant differential abundance and those ranked by the machine learning model participate in enriched biological processes that correspond to known pathophysiological and cellular mechanisms that contribute to AKI, suggesting that those proteins can serve as potential biomarkers to be further verified and validated for AKI diagnosis. Comparison of the plasma and previously generated urinary proteome profiles showed five proteins with significant differences in abundance that overlapped both proteomes providing evidence for the renal physiological dynamics of these proteins in renal injury and disease. Significance: Improving the detection of ARV-associated nephrotoxicity is challenging because current serum creatinine (srCr) based-equations used to estimate the glomerular filtration rate (eGFR) for assessing kidney function have been reported to overestimate the eGFR in the South African population and changes in srCr measurements also reflect a delayed response to the initial structural injury of the kidney. This hinders the timeous detection of ARV-associated nephrotoxicity which can lead to irreversible renal damage and can compromise the continuation of treatment in PLHIV, thus emphasising the need to introduce novel AKI biomarkers to mitigate ARV-associated nephrotoxicity in at risk PLHIV in South Africa. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/605118v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@18743eaorg.highwire.dtl.DTLVardef@17bba7borg.highwire.dtl.DTLVardef@101c78org.highwire.dtl.DTLVardef@1bd2b23_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIIdentified thirty-four proteins with significant changes in abundance between study groups. C_LIO_LIMachine learning showed fourteen proteins associated with renal disease biology that differentiate the study groups. C_LIO_LIFirst study to analyse plasma proteome of this cohort of PLHIV in South Africa C_LIO_LIFive proteins overlap the plasma and urinary proteome profiles of the study groups. C_LI

biochemistry↗

bioRxiv2024

Proteomic analysis identifies dysregulated proteins in albuminuria: a South African pilot study

Albuminuria may precede decreases in glomerular filtration rate (GFR) and both tests are insensitive predictors of early stages of kidney disease. Our aim was to characterise the urinary proteome in black African individuals with albuminuria and well-preserved GFR from South Africa. A case-controlled study that compared urinary proteomes of 52 normoalbuminuric (urine albumin: creatinine ratio (uACR) <3 mg/mmol) and 56 albuminuric (uACR [≥] 3 mg/mmol) adults of Black African ethnicity. Urine proteins were precipitated, reduced, alkylated, digested, and analysed using an Evosep One LC coupled to a Sciex 5600 Triple-TOF in data-independent acquisition mode. Data were searched on SpectronautTM 15. Differentially abundant proteins (DAPs) were filtered [≥] 2.25-fold change and false discovery rate [≤] 1%. Receiver operating characteristic curves were used to assess the discriminating ability of proteins of interest. Pathway analysis was performed using Enrichr software. The albuminuric group had a higher uACR (7.9 vs 0.55 mg/mmol, p <0.001). The median eGFR (mL/min/1.73m2) showed no difference between the groups (111 vs 114, p=0.707). We identified 80 DAPs in the albuminuria group compared to normoalbuminuria, of which 59 proteins increased while 21 proteins decreased in abundance. We found 12 urinary proteins with AUC > 0.8, and p-value <0.001 in the multivariate analysis. Furthermore, an 80-protein model was developed that showed a high AUC >0.907 and a predictive accuracy of 91.3% between the two groups. Pathway analysis associated with DAPs were involved in insulin growth factor (IGF) functions, innate immunity, platelet degranulation, and extracellular matrix organization. In albuminuric individuals with well-preserved eGFR, pathways involved in preventing the release and uptake of IGF by insulin growth factor binding protein were significantly enriched. These proteins are indicative of a homeostatic imbalance in a variety of cellular processes underlying renal dysfunction and are implicated in chronic kidney disease.

biochemistry↗

bioRxiv2023

Urine-HILIC: Automated sample preparation for bottom-up urinary proteome profiling in clinical proteomics

Urine provides a diverse source of information related to a patients health status and is ideal for clinical proteomics because of its ease of collection. To date, there is no standard operating procedure for reproducible and robust urine sample preparation for mass spectrometry-based clinical proteomics. To this end, a novel workflow was developed based on an on-bead protein capture, clean up, and digestion without the requirement for processing steps such as precipitation or centrifugation. The workflow was applied to an acute kidney injury (AKI) pilot study. Urine from clinical samples and a pooled sample were subjected to automated sample preparation in a KingFisher Flex magnetic handling station using a novel urine-HILIC (uHLC) approach based on MagReSyn(R) HILIC microspheres. For benchmarking, the pooled sample was also prepared using a published protocol based on an on-membrane (OM) protein capture and digestion workflow. Peptides were analysed by LCMS in data independent acquisition (DIA) mode using a Dionex Ultimate 3000 UPLC coupled to a Sciex 5600 mass spectrometer. Data was searched in Spectronaut 17. Both workflows showed similar peptide and protein identifications in the pooled sample. The uHLC workflow was easier to set up and complete, having less hands-on time than the OM method, with fewer manual processing steps. Lower peptide and protein CV was observed in the uHLC technical replicates. Following statistical analysis, candidate protein markers were filtered, at [≥] 2-fold change in abundance, [≥] 2 unique peptides and [≤] 1% false discovery rate, and revealed many significant, differentially abundant kidney injury-associated urinary proteins. The pilot data derived using this novel workflow provides information on the urinary proteome of patients with AKI. Further exploration in a larger cohort using this novel high-throughput method is warranted.

biochemistry↗

bioRxiv2023

Mag-Net: Rapid enrichment of membrane-bound particles enables high coverage quantitative analysis of the plasma proteome

Membrane-bound particles in plasma are composed of exosomes, microvesicles, and apoptotic bodies and represent [~]1-2% of the total protein composition. Proteomic interrogation of this subset of plasma proteins augments the representation of tissue-specific proteins, representing a "liquid biopsy," while enabling the detection of proteins that would otherwise be beyond the dynamic range of liquid chromatography-tandem mass spectrometry of unfractionated plasma. We have developed an enrichment strategy (Mag-Net) using hyper-porous strong-anion exchange magnetic microparticles to sieve membrane-bound particles from plasma. The Mag-Net method is robust, reproducible, inexpensive, and requires <100 L plasma input. Coupled to a quantitative data-independent mass spectrometry analytical strategy, we demonstrate that we can collect results for >37,000 peptides from >4,000 plasma proteins with high precision. Using this analytical pipeline on a small cohort of patients with neurodegenerative disease and healthy age-matched controls, we discovered 204 proteins that differentiate (q-value < 0.05) patients with Alzheimers disease dementia (ADD) from those without ADD. Our method also discovered 310 proteins that were different between Parkinsons disease and those with either ADD or healthy cognitively normal individuals. Using machine learning we were able to distinguish between ADD and not ADD with a mean ROC AUC = 0.98 {+/-} 0.06.

biochemistry↗

bioRxiv2020

Zirconium(IV)-IMAC for phosphopeptide enrichment in phosphoproteomics

Phosphopeptide enrichment is an essential step in large-scale, quantitative phosphoproteomics studies by mass spectrometry. Several phosphopeptide affinity enrichment techniques exist, such as Immobilized Metal ion Affinity Chromatography (IMAC) and Metal Oxide Affinity Chromatography (MOAC). We compared Zirconium (IV) IMAC (Zr-IMAC) magnetic microparticles to more commonly used Titanium (IV) IMAC (Ti-IMAC) and TiO2 magnetic microparticles for phosphopeptide enrichment from simple and complex protein samples prior phosphopeptide sequencing and characterization by mass spectrometry (LC-MS/MS). We optimized sample-loading conditions to increase phosphopeptide recovery for Zr-IMAC, Ti-IMAC and TiO2 based workflows. The performance of Zr-IMAC was enhanced by 19-22% to recover up to 5173 phosphopeptides from 200 {micro}g of protein extract from HepG2/C3A cells, making Zr-IMAC the preferred method for phosphopeptide enrichment in this study. Ti-IMAC and TiO2 performance were also optimized to improve phosphopeptide numbers by 28% and 35%, respectively. Furthermore, Zr-IMAC based phosphoproteomics in the magnetic microsphere format identified 23% more phosphopeptides than HPLC-based Fe(III)-IMAC for same sample amount (200 {micro}g), thereby adding 37% more uniquely identified phosphopeptides. We conclude that Zr-IMAC improves phosphoproteome coverage and recommend that this affinity enrichment method should be more widely used in biological and biomedical studies of cell signalling and in the search for disease-biomarkers.

biochemistry↗