From Obesity to Diabetes: Uncovering Molecular Connections Sketching Proteomics, A Narrative Review
Article Sidebar
Main Article Content
Abstract
Background: Recent research has illuminated the pivotal role of low-grade inflammation in metabolic diseases such as obesity and diabetes, with gut microbiota dysbiosis playing a key role. Metaproteomics offers a novel lens to explore these interactions by profiling protein compositions in microbial communities, revealing insights into the metabolic disruptions that accompany these conditions.
Objective: This study aims to compile and analyze existing metaproteomic research related to obesity and both types of diabetes, identifying specific metaproteomic alterations that correlate with these metabolic diseases.
Methods: Adhering to PRISMA guidelines, a rigorous selection process was employed to gather relevant studies on the metaproteomics of obesity and diabetes. This involved analyzing microbial and human protein alterations, focusing on patterns consistently observed in these diseases.
Results: Analysis identified unique metaproteomic signatures associated with obesity and diabetes, highlighting both microbial and human proteins. Specifically, alterations in proteins involved in carbohydrate metabolism and inflammation were recurrent. Despite the identification of up- or down-regulated proteins across studies, the limited breadth of comprehensive metaproteomic data restricts definitive conclusions.
Conclusion: Metaproteomics has shed light on the intricate metabolic disturbances in obesity and diabetes. However, the discipline remains nascent, necessitating further development of specialized databases and standardized methodologies to deepen our understanding and treatment of these complex diseases.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Aron-Wisnewsky, J.; Prifti, E.; Belda, E.; Ichou, F.; Kayser, B.D.; Dao, M.C.; Verger, E.O.; Hedjazi, L.; Bouillot, J.-L.; Chevallier, J.-M.; et al. Major Microbiota Dysbiosis in Severe Obesity: Fate after Bariatric Surgery. Gut 2019, 68, 70–82.
Cénit, M.C.; Matzaraki, V.; Tigchelaar, E.F.; Zhernakova, A. Rapidly Expanding Knowledge on the Role of the Gut Microbiome in Health and Disease. Biochim. Biophys. Acta (BBA) Mol. Basis Dis. 2014, 1842, 1981–1992.
Ezzeldin, S.; El-Wazir, A.; Enany, S.; Muhammad, A.; Johar, D.; Osama, A.; Ahmed, E.; Shikshaky, H.; Magdeldin, S. Current Understanding of Human Metaproteome Association and Modulation. J. Proteome Res. 2019, 18, 3539–3554.
Round, J.L.; Mazmanian, S.K. The Gut Microbiota Shapes Intestinal Immune Responses during Health and Disease. Nat. Rev. Immunol. 2009, 9, 313–323.
Erickson, A.R.; Cantarel, B.L.; Lamendella, R.; Darzi, Y.; Mongodin, E.F.; Pan, C.; Shah, M.; Halfvarson, J.; Tysk, C.; Henrissat, B.; et al. Integrated Metagenomics/Metaproteomics Reveals Human Host-Microbiota Signatures of Crohn’s Disease. PLoS ONE 2012, 7, e49138.
Petriz, B.A.; Franco, O.L. Metaproteomics as a Complementary Approach to Gut Microbiota in Health and Disease. Front. Chem.2017, 5, 4.
King, G.L. The Role of Inflammatory Cytokines in Diabetes and Its Complications. J. Periodontol. 2008, 79, 1527–1534.
Balistreri, C.R.; Caruso, C.; Candore, G. The Role of Adipose Tissue and Adipokines in Obesity-Related Inflammatory Diseases. Mediat. Inflamm. 2010, 2010, e802078.
Monnerie, S.; Comte, B.; Ziegler, D.; Morais, J.A.; Pujos-Guillot, E.; Gaudreau, P. Metabolomic and Lipidomic Signatures of Metabolic Syndrome and Its Physiological Components in Adults: A Systematic Review. Sci. Rep. 2020, 10, 669.
Pinart, M.; Nimptsch, K.; Forslund, S.K.; Schlicht, K.; Gueimonde, M.; Brigidi, P.; Turroni, S.; Ahrens, W.; Hebestreit, A.; Wolters, M.; et al. Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis. Nutrients 2021, 13, 3292. [CrossRef]
Marcon, Y.; Bishop, T.; Avraam, D.; Escriba-Montagut, X.; Ryser-Welch, P.; Wheater, S.; Burton, P.; González, J.R. Orchestrating Privacy-Protected Big Data Analyses of Data from Different Resources with R and DataSHIELD. PLoS Comput. Biol. 2021, 17
Shamseer, L.; Moher, D.; Clarke, M.; Ghersi, D.; Liberati, A.; Petticrew, M.; Shekelle, P.; Stewart, L.A. Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) 2015: Elaboration and Explanation. BMJ 2015, 349,
Pinto, E.; Anselmo, M.; Calha, M.; Bottrill, A.; Duarte, I.; Andrew, P.W.; Faleiro, M.L. The Intestinal Proteome of Diabetic and Control Children Is Enriched with Different Microbial and Host Proteins. Microbiology 2017, 163, 161–17
Ferrer, M.; Ruiz, A.; Lanza, F.; Haange, S.-B.; Oberbach, A.; Till, H.; Bargiela, R.; Campoy, C.; Segura, M.T.; Richter, M.; et al. Microbiota from the Distal Guts of Lean and Obese Adolescents Exhibit Partial Functional Redundancy besides Clear Differences in Community Structure. Environ. Microbiol. 2013, 15, 211–226.
Kolmeder, C.A.; Ritari, J.; Verdam, F.J.; Muth, T.; Keskitalo, S.; Varjosalo, M.; Fuentes, S.; Greve, J.W.; Buurman, W.A.; Reichl, U.; et al. Colonic Metaproteomic Signatures of Active Bacteria and the Host in Obesity. Proteomics 2015, 15, 3544–3552.
Heintz-Buschart, A.; May, P.; Laczny, C.C.; Lebrun, L.A.; Bellora, C.; Krishna, A.; Wampach, L.; Schneider, J.G.; Hogan, A.; de Beaufort, C.; et al. Integrated Multi-Omics of the Human Gut Microbiome in a Case Study of Familial Type 1 Diabetes. Nat. Microbiol. 2016, 2, 1–13.
Sanchez-Carrillo, S.; Ciordia, S.; Rojo, D.; Zubeldia-Varela, E.; Méndez-García, C.; Martínez-Martínez, M.; Barbas, C.; Ruiz-Ruiz, S.; Moya, A.; Garriga, M.; et al. A Body Weight Loss- and Health-Promoting Gut Microbiota Is Established after Bariatric Surgery in Individuals with Severe Obesity. J. Pharm. Biomed. Anal. 2021, 193, 113747.
Gavin, P.G.; Mullaney, J.A.; Loo, D.; Cao, K.-A.L.; Gottlieb, P.A.; Hill, M.M.; Zipris, D.; Hamilton-Williams, E.E. Intestinal Metaproteomics Reveals Host-Microbiota Interactions in Subjects at Risk for Type 1 Diabetes. Diabetes Care 2018, 41, 2178–2186.
Foster, T.P.; Bruggeman, B.; Campbell-Thompson, M.; Atkinson, M.A.; Haller, M.J.; Schatz, D.A. Exocrine Pancreas Dysfunction in Type 1 Diabetes. Endocr. Pract. 2020, 26, 1505–1513.
Kondrashova, A.; Nurminen, N.; Lehtonen, J.; Hyöty, M.; Toppari, J.; Ilonen, J.; Veijola, R.; Knip, M.; Hyöty, H. Exocrine Pancreas Function Decreases during the Progression of the Beta-Cell Damaging Process in Young Prediabetic Children. Pediatr. Diabetes 2018, 19, 398–402.
Dozio, N.; Indirli, R.; Giamporcaro, G.M.; Frosio, L.; Mandelli, A.; Laurenzi, A.; Bolla, A.M.; Stabilini, A.; Valle, A.; Locatelli, M.; et al. Impaired Exocrine Pancreatic Function in Different Stages of Type 1 Diabetes. BMJ Open Diabetes Res. Care 2021, 9, e001158.
Alkanani, A.K.; Hara, N.; Gottlieb, P.A.; Ir, D.; Robertson, C.E.; Wagner, B.D.; Frank, D.N.; Zipris, D. Alterations in Intestinal Microbiota Correlate With Susceptibility to Type 1 Diabetes. Diabetes 2015, 64, 3510–3520.
Harbison, J.E.; Roth-Schulze, A.J.; Giles, L.C.; Tran, C.D.; Ngui, K.M.; Penno, M.A.; Thomson, R.L.; Wentworth, J.M.; Colman, P.G.; Craig, M.E.; et al. Gut Microbiome Dysbiosis and Increased Intestinal Permeability in Children with Islet Autoimmunity and Type 1 Diabetes: A Prospective Cohort Study. Pediatr. Diabetes 2019, 20, 574–583.
Hebert, S.L.; Nair, K.S. Protein and Energy Metabolism in Type 1 Diabetes. Clin. Nutr. 2010, 29, 13–17.
Holecˇek, M. Branched-Chain Amino Acids and Branched-Chain Keto Acids in Hyperammonemic States: Metabolism and as Supplements. Metabolites 2020, 10, 324.
Aschner, P.J.; Ruiz, A.J. Metabolic Memory for Vascular Disease in Diabetes. Diabetes Technol. Ther. 2012, 14, S68–S74.
Timmins-Schiffman, E.; May, D.H.; Mikan, M.; Riffle, M.; Frazar, C.; Harvey, H.R.; Noble, W.S.; Nunn, B.L. Critical Decisions in Metaproteomics: Achieving High Confidence Protein Annotations in a Sea of Unknowns. ISME J. 2017, 11, 309–314.
Werner, J.; Géron, A.; Kerssemakers, J.; Matallana-Surget, S. MPies: A Novel Metaproteomics Tool for the Creation of Relevant Protein Databases and Automatized Protein Annotation. Biol. Direct 2019, 14, 21.
Hyatt, D.; LoCascio, P.F.; Hauser, L.J.; Uberbacher, E.C. Gene and Translation Initiation Site Prediction in Metagenomic Sequences. Bioinformatics 2012, 28, 2223–2230.
Ahmad, A.; Yang, W.; Chen, G.; Shafiq, M.; Javed, S.; Zaidi, S.S.A.; Shahid, R.; Liu, C.; Bokhari, H. Analysis of Gut Microbiota of Obese Individuals with Type 2 Diabetes and Healthy Individuals. PLoS ONE 2019, 14, e0226372.
Hernández E, Bargiela R, Diez MS, Friedrichs A, Pérez-Cobas AE, Gosalbes MJ, Knecht H, Martínez-Martínez M, Seifert J, Von Bergen M, Artacho A. Functional consequences of microbial shifts in the human gastrointestinal tract linked to antibiotic treatment and obesity. Gut microbes. 2013 Jul 12;4(4):306-15.
Zhou W, Sailani MR, Contrepois K, Zhou Y, Ahadi S, Leopold SR, Zhang MJ, Rao V, Avina M, Mishra T, Johnson J. Longitudinal multi-omics of host–microbe dynamics in prediabetes. Nature. 2019 May 30;569(7758):663-71.
Zhong H, Ren H, Lu Y, Fang C, Hou G, Yang Z, Chen B, Yang F, Zhao Y, Shi Z, Zhou B. Distinct gut metagenomics and metaproteomics signatures in prediabetics and treatment-naïve type 2 diabetics. EBioMedicine. 2019 Sep 1;47:373-83.