Maulucci Giuseppe, Cordelli Ermanno, Rizzi Alessandro, De Leva Francesca, Papi Massimiliano, Ciasca Gabriele, Samengo Daniela, Pani Giovambattista, Pitocco Dario, Soda Paolo, Ghirlanda Giovanni, Iannello Giulio, De Spirito Marco
Istituto di Fisica, Università Cattolica del Sacro Cuore, Rome, Italy.
Unità di Sistemi di elaborazione e bioinformatica, Facoltà dipartimentale di Ingegneria, Università Campus Bio-Medico, Rome, Italy.
PLoS One. 2017 Sep 7;12(9):e0184109. doi: 10.1371/journal.pone.0184109. eCollection 2017.
Glycosylation, oxidation and other post-translational modifications of membrane and transmembrane proteins can alter lipid density, packing and interactions, and are considered an important factor that affects fluidity variation in membranes. Red blood cells (RBC) membrane physical state, showing pronounced alterations in Type 1 diabetes mellitus (T1DM), could be the ideal candidate for monitoring the disease progression and the effects of therapies. On these grounds, the measurement of RBC membrane fluidity alterations can furnish a more sensitive index in T1DM diagnosis and disease progression than Glycosylated hemoglobin (HbA1c), which reflects only the information related to glycosylation processes. Here, through a functional two-photon microscopy approach we retrieved fluidity maps at submicrometric scale in RBC of T1DM patients with and without complications, detecting an altered membrane equilibrium. We found that a phase separation between fluid and rigid domains occurs, triggered by systemic effects on membranes fluidity of glycation and oxidation. The phase separation patterns are different among healthy, T1DM and T1DM with complications patients. Blood cholesterol and LDL content are positively correlated with the extent of the phase separation patterns. To quantify this extent a machine learning approach is employed to develop a Decision-Support-System (DSS) able to recognize different fluidity patterns in RBC. Preliminary analysis shows significant differences(p<0.001) among healthy, T1DM and T1DM with complications patients. The development of an assay based on Phase separation of the plasma membrane of the Red Blood cells is a potential tool for diagnosis and progression monitoring of type 1 diabetes mellitus, and could allow customization and the selection of medical treatments in T1DM in clinical settings, and enable the early detection of complications.
膜蛋白和跨膜蛋白的糖基化、氧化及其他翻译后修饰可改变脂质密度、堆积和相互作用,被认为是影响膜流动性变化的重要因素。红细胞(RBC)膜的物理状态在1型糖尿病(T1DM)中表现出明显改变,可能是监测疾病进展和治疗效果的理想候选者。基于这些理由,测量RBC膜流动性改变可为T1DM诊断和疾病进展提供比糖化血红蛋白(HbA1c)更敏感的指标,后者仅反映与糖基化过程相关的信息。在此,我们通过功能性双光子显微镜方法获取了有并发症和无并发症的T1DM患者RBC中亚微米尺度的流动性图谱,检测到膜平衡改变。我们发现,由糖基化和氧化对膜流动性的系统性影响引发了流体域和刚性域之间的相分离。健康患者、T1DM患者和有并发症的T1DM患者的相分离模式不同。血液胆固醇和低密度脂蛋白含量与相分离模式的程度呈正相关。为了量化这种程度,采用机器学习方法开发了一个决策支持系统(DSS),能够识别RBC中不同的流动性模式。初步分析显示健康患者、T1DM患者和有并发症的T1DM患者之间存在显著差异(p<0.001)。基于红细胞质膜相分离开发的检测方法是1型糖尿病诊断和进展监测的潜在工具,可在临床环境中实现T1DM医疗治疗的定制和选择,并能早期发现并发症。