1.
Innate immune remodeling by short-term intensive fasting.
Qian, J, Fang, Y, Yuan, N, Gao, X, Lv, Y, Zhao, C, Zhang, S, Li, Q, Li, L, Xu, L, et al
Aging cell. 2021;(11):e13507
Abstract
Previous studies have shown that long-term light or moderate fasting such as intermittent fasting can improve health and prolong lifespan. However, in humans short-term intensive fasting, a complete water-only fasting has little been studied. Here, we used multi-omics tools to evaluate the impact of short-term intensive fasting on immune function by comparison of the CD45+ leukocytes from the fasting subjects before and after 72-h fasting. Transcriptomic and proteomic profiling of CD45+ leukocytes revealed extensive expression changes, marked by higher gene upregulation than downregulation after fasting. Functional enrichment of differentially expressed genes and proteins exposed several pathways critical to metabolic and immune cell functions. Specifically, short-term intensive fasting enhanced autophagy levels through upregulation of key members involved in the upstream signals and within the autophagy machinery, whereas apoptosis was reduced by down-turning of apoptotic gene expression, thereby increasing the leukocyte viability. When focusing on specific leukocyte populations, peripheral neutrophils are noticeably increased by short-term intensive fasting. Finally, proteomic analysis of leukocytes showed that short-term intensive fasting not only increased neutrophil degranulation, but also increased cytokine secretion. Our results suggest that short-term intensive fasting boost immune function, in particular innate immune function, at least in part by remodeling leukocytes expression profile.
2.
Small-protein Enrichment Assay Enables the Rapid, Unbiased Analysis of Over 100 Low Abundance Factors from Human Plasma.
Harney, DJ, Hutchison, AT, Su, Z, Hatchwell, L, Heilbronn, LK, Hocking, S, James, DE, Larance, M
Molecular & cellular proteomics : MCP. 2019;(9):1899-1915
Abstract
Unbiased and sensitive quantification of low abundance small proteins in human plasma (e.g. hormones, immune factors, metabolic regulators) remains an unmet need. These small protein factors are typically analyzed individually and using antibodies that can lack specificity. Mass spectrometry (MS)-based proteomics has the potential to address these problems, however the analysis of plasma by MS is plagued by the extremely large dynamic range of this body fluid, with protein abundances spanning at least 13 orders of magnitude. Here we describe an enrichment assay (SPEA), that greatly simplifies the plasma dynamic range problem by enriching small-proteins of 2-10 kDa, enabling the rapid, specific and sensitive quantification of >100 small-protein factors in a single untargeted LC-MS/MS acquisition. Applying this method to perform deep-proteome profiling of human plasma we identify C5ORF46 as a previously uncharacterized human plasma protein. We further demonstrate the reproducibility of our workflow for low abundance protein analysis using a stable-isotope labeled protein standard of insulin spiked into human plasma. SPEA provides the ability to study numerous important hormones in a single rapid assay, which we applied to study the intermittent fasting response and observed several unexpected changes including decreased plasma abundance of the iron homeostasis regulator hepcidin.
3.
Beta cell function in type 1 diabetes determined from clinical and fasting biochemical variables.
Wentworth, JM, Bediaga, NG, Giles, LC, Ehlers, M, Gitelman, SE, Geyer, S, Evans-Molina, C, Harrison, LC, , , ,
Diabetologia. 2019;(1):33-40
-
-
Free full text
-
Abstract
AIMS/HYPOTHESIS Beta cell function in type 1 diabetes is commonly assessed as the average plasma C-peptide concentration over 2 h following a mixed-meal test (CPAVE). Monitoring of disease progression and response to disease-modifying therapy would benefit from a simpler, more convenient and less costly measure. Therefore, we determined whether CPAVE could be reliably estimated from routine clinical variables. METHODS Clinical and fasting biochemical data from eight randomised therapy trials involving participants with recently diagnosed type 1 diabetes were used to develop and validate linear models to estimate CPAVE and to test their accuracy in estimating loss of beta cell function and response to immune therapy. RESULTS A model based on disease duration, BMI, insulin dose, HbA1c, fasting plasma C-peptide and fasting plasma glucose most accurately estimated loss of beta cell function (area under the receiver operating characteristic curve [AUROC] 0.89 [95% CI 0.87, 0.92]) and was superior to the commonly used insulin-dose-adjusted HbA1c (IDAA1c) measure (AUROC 0.72 [95% CI 0.68, 0.76]). Model-estimated CPAVE (CPEST) reliably identified treatment effects in randomised trials. CPEST, compared with CPAVE, required only a modest (up to 17%) increase in sample size for equivalent statistical power. CONCLUSIONS/INTERPRETATION CPEST, approximated from six variables at a single time point, accurately identifies loss of beta cell function in type 1 diabetes and is comparable to CPAVE for identifying treatment effects. CPEST could serve as a convenient and economical measure of beta cell function in the clinic and as a primary outcome measure in trials of disease-modifying therapy in type 1 diabetes.