Timothy D. Cummins

Visith Thongboonkerd

Frontiers in Physiology

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Editorial: Proteomics, massspectrometry and bioinformaticsin renal pathophysiologyTimothy D. Cummins1* and Visith Thongboonkerd2*1Division of Nephrology and Hypertension, Department of Medicine, and Clinical Proteomics Center,University of Louisville, Louisville, KY, United States, 2Medical Proteomics Unit, Research Department,Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, ThailandKEYWORDSbioinformatics, biomarker, mass spectrometry, proteomics, renal pathology, renalphysiologyEditorial on the Research TopicProteomics, mass spectrometry and bioinformatics in renalpathophysiologyDuring the past 2 decades, proteomics, mass spectrometry and bioinformatics have beenwidely applied to study various kidney diseases, e.g., acute kidney injury (AKI), chronickidney disease (CKD), diabetic kidney disease (DKD), and glomerular diseases. Suchapplications will surely lead to breakthroughs in mechanistic insights, biomarker targetsfor diagnostics/prognostics and best clinical practice. This Research Topic on proteomics,mass spectrometry and bioinformatics in renal pathophysiology offers a 5-paper selectionanalyses of a variety of kidney diseases using different Omics and bioinformatics approaches.Zhu et al. provide in-depth plasma metabolomics analysis of 31 CKD patients withoutdialysis (or pre-dialysis) compared with 31 and 30 CKD patients who are on hemodialysis (HD)and peritoneal dialysis (PD), respectively. This approach provides important data on the plasmametabolome in CKD and its alterations by HD and PD. Insights into the disease mechanismsmay be revealed using these detailed metabolomic findings to define the critical changes inmetabolites (i.e., enzyme activity) that occur during disease progression and response to differentmodalities of the dialysis treatment. For example, metabolites related to cysteine metabolismpredominantly differ between the pre-dialysis patients and those who are on HD or PD, whereasmetabolites related to purine metabolism largely differ between the HD and PD groups. Theseresults suggest useful metabolite candidates towards managing Stage 5 CKD patients with someinsights into precision medicine, which may be more feasible by using more in-depth informaticanalyses together with the targeted metabolite studies.The Omics studies often generate large datasets with untapped information that can begleaned with a deep-dive informatics modeling approach. Cai et al. provide a bioinformaticsanalysis identifying genes implicated in the immune response ofmembranous nephropathy (MN).Microarray datasets of 65MN patients and 9 healthy individuals from the Gene ExpressionOmnibus database are mined for deeper insights. Using linear model for microarray data(LIMMA) and enrichment approaches, 370 differentially expressed genes in MN and 20 hubgenes of their interacting network have been elucidated. Some of these bioinformatic data can beconfirmed by experimental approaches (i.e., immunohistochemistry). These data clearly show thatmining existing datasets is imperative towards improving our understanding and depth of theknowledge on the renal pathophysiology.OPEN ACCESSEDITED AND REVIEWED BYCarolyn Mary Ecelbarger,Georgetown University, United States*CORRESPONDENCETimothy D. Cummins,timothy.cummins@louisville.eduVisith Thongboonkerd,thongboonkerd@dr.com,vthongbo@yahoo.comRECEIVED 14 November 2023ACCEPTED 15 November 2023PUBLISHED 23 November 2023CITATIONCummins TD and Thongboonkerd V(2023), Editorial: Proteomics, massspectrometry and bioinformatics inrenal pathophysiology.Front. Physiol. 14:1338270.doi: 10.3389/fphys.2023.1338270COPYRIGHT© 2023 Cummins and Thongboonkerd.This is an open-access article distributedunder the terms of the CreativeCommons Attribution License (CC BY).The use, distribution or reproduction inother forums is permitted, provided theoriginal author(s) and the copyrightowner(s) are credited and that the originalpublication in this journal is cited, inaccordance with accepted academicpractice. No use, distribution orreproduction is permitted which does notcomply with these terms.Frontiers in Physiology frontiersin.org01TYPE EditorialPUBLISHED 23 November 2023DOI 10.3389/fphys.2023.1338270Implementation of the Omics approaches to improve decisionmaking in clinical practice is a promise of precision medicine thatbegins to be more fully realized with better Omics utilization. Earlyprecise decision making in the clinical toolkit will provide more targetedand efficacious treatments. Citrate dialysate has been shown to improveclinical outcome in HD patients, but the mechanisms of action arepoorly understood. Broseta et al. provide a metabolomics analysis ofplasma for improved understanding of utilizing citrate dialysatecompared with acetate dialysate. Plasma metabolites are collectedfrom pre, mid, immediately post and 30-min-post HD to provide asequential profiling analysis and to determine differences from usingdifferent dialysates. Their analyses have revealed that citrate dialysateoffers a better clearance ofmetabolites that belong to uremic toxins whileincreases the post-dialysis branched-chain amino acids. Moreover,citrate exclusively decreases metabolites related to lysine degradation,whereas the increased clearance of acylcarnitines is unique for acetatedialysate. These findings underscore that large-scale metabolomeanalysis can enhance our understanding of different therapeuticoutcomes of dialysis using various kinds of dialysates as reflected bydifferential changes in the post-dialysis plasma metabolome.Understanding the renal pathophysiology requires comprehensiveanalysis of all aspects of the kidney function at tissue, organ and cellularlevels. Tools developed for analysis of transcriptomics, proteomics,metabolomics and lipidomics can often be cross-utilized for datamining and statistical interrogation. Development of single-cellanalytical techniques allows for detailed mapping and delineation oforigins of the disease pathophysiology. Mao et al. review the recenttechnological advances in single-cell transcriptomics and provide anoverview of its application towards a better understanding of thepathophysiology of DKD specifically. Cell-type specific informationin the context of changes in transcript level can give a precise molecularmap or snapshot of the disease mechanisms. Integration of single-cellproteomics, metabolomics and transcriptomics can provide the mostrobust analysis, to date, and hence will be amajor undertaking in a renalcontext to give a precision overview of cellular changes inDKD (and therenal pathophysiology in general).Modeling of human diseases is a difficult but worthwhileundertaking when development of animal models in conjunctionwith the Omics methodology can be implemented to improve ourunderstanding of complex kidney diseases. Exertional heat stroke(EHS)-induced AKI is prevalent in equatorial countries with largeagriculture sectors, and biomarker efforts can benefit early andtargeted treatment strategies. Understanding the onset of AKI withbiomarkers can prevent or reduce effects of the EHS-induced AKI.Wenet al. pursue a proteomics analysis of the EHS-induced AKI in a ratmodel to determine candidate protein biomarkers of the disease onset.The analysis has revealed 3,129 differentially expressed proteins in EHS-induced AKI. Among these, 10 significantly modulated and disease-related targets can be verified in rat renal tissue and urine byquantitative RT-PCR and Western blotting. The initial analyses frommodel organisms and further translation into human diseases will be acritical step for implementing from pre-clinical target identification tobed-side clinical utility. The application and expansion of theseapproaches in diverse pre-clinical experiments will be importanttowards better and more precise utilization of proteomics technologyin addressing gaps in our understanding of various kidney diseases.Overall, the implementation of various Omics technologies tomore comprehensively understand kidney biology andpathophysiology has taken great strides in the last 25 years. Basicresearch is now reaching the clinic and providing better decision-making tools and information to improve therapeutic outcome andpatients’ quality of life and survival through critical stages of illness.Nevertheless, the promise of precision medicine is not fullyimplemented in the clinic and will take many more dedicatedresearch efforts and translational applications to be better utilizedfor improving the therapeutic outcome. This Research Topic onlyhighlights a few technical examples of the breadth of approaches andmodels for utilizing the Omics technologies in pre-clinical andclinical settings. Improvements in research methodology andbioinformatics mining approaches will undoubtedly lead to evenmore interesting and groundbreaking insights into the renalpathophysiology.Author contributionsTC: Writing–original draft, Writing–review and editing. VT:Writing–original draft, Writing–review and editing.FundingThe author(s) declare financial support was received for theresearch, authorship, and/or publication of this article. TDC is partlysupported by the National Institutes of Health (5R01DK110077) theUniversity of Louisville Kidney Disease Program and the NephcureKidney International-Pediatric Nephrology Research Consortium(NKI-PNRC 2023-04). VT is supported by the National ResearchCouncil of Thailand (NRCT): High-Potential Research Team GrantProgram (N42A660625).AcknowledgmentsWe are grateful to all the authors and reviewers for theircontributions to this Research Topic.Conflict of interestThe authors declare that the research was conducted in theabsence of any commercial or financial relationships that could beconstrued as a potential conflict of interest.The author(s) declared that they were an editorial boardmember of Frontiers, at the time of submission. This had noimpact on the peer review process and the final decision.Publisher’s noteAll claims expressed in this article are solely those of the authorsand do not necessarily represent those of their affiliatedorganizations, or those of the publisher, the editors and thereviewers. Any product that may be evaluated in this article, orclaim that may be made by its manufacturer, is not guaranteed orendorsed by the publisher.Frontiers in Physiology frontiersin.org02Cummins and Thongboonkerd 10.3389/fphys.2023.1338270

Editorial: Proteomics, mass spectrometry and bioinformatics in renal pathophysiology

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Editorial: Proteomics, mass spectrometry and bioinformatics in renal pathophysiology

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