Novel phage display-derived mycolic acid-specific antibodies with potential for tuberculosis diagnosis

Tuberculosis is a major cause of mortality and morbidity due to infectious disease. However, current clinical diagnostic methodologies such as PCR, sputum culture, or smear microscopy are not ideal. Antibody-based assays are a suitable alternative but require specific antibodies against a suitable biomarker. Mycolic acid, which has been found in patient sputum samples and comprises a large portion of the mycobacterial cell wall, is an ideal target. However, generating anti-lipid antibodies using traditional hybridoma methodologies is challenging and has limited the exploitation of this lipid as a diagnostic marker. We describe here the isolation and characterization of four anti-mycolic acid antibodies from a nonimmune antibody phage display library that can detect mycolic acids down to a limit of 4.5ng. All antibodies were specific for the methoxy subclass of mycolic acid with weak binding for α mycolic acid and did not show any binding to closely related lipids or other Mycobacterium tuberculosis (Mtb) derived lipids. We also determined the clinical utility of these antibodies based on their limit of detection for mycobacteria colony forming units (CFU). In combination with an optimized alkaline hydrolysis method for rapid lipid extraction, these antibodies can detect 10⁵ CFU of Mycobacterium bovis BCG, a close relative of Mtb and therefore represent a novel approach for the development of diagnostic assays for lipid biomarkers.     

Tracking fatty acid kinetics in distinct lipoprotein fractions in vivo: a novel high-throughput approach for studying dyslipidemia in rodent models

Isotopic tracers have been used to examine lipid trafficking for many years, and data from those studies have typically yielded novel insight regarding the pathophysiology of dyslipidemia. Previous experimental designs were suitable for studies in humans because relatively large volumes of plasma could be regularly sampled. We have expanded on the earlier logic by applying high-throughput analytical methods that require reduced sample volumes. Specifically, we have examined the possibility of coupling gel-based separations of lipoproteins (e.g., lipoprint) with LC-MS/MS analyses of complex lipid mixtures as a way to routinely measure the labeling profiles of distinct lipids in discrete lipoprotein subfractions. We demonstrate the ability to measure the incorporation of [U-¹³C]oleate into triglycerides (TG), PLs (PL), and cholesterol esters (CE) in VLDL, LDL, and HDL particles in mice. Although rodent models of dyslipidemia are inherently different from humans because of alterations in enzyme activities and underlying metabolism, rodent models can be used to screen novel compounds for efficacy in altering a given biochemical pathway and therein enable studies of target engagement in vivo. We expect that it is possible to translate our approach for application in other systems, including studies in humans.     

肺癌早期诊断的研究进展

大多数肺癌患者在确诊时已属中晚期,5年生存率极低,早期诊断是改善其预后和提高生存率的关键。目前常用的肺癌早期诊断方法包括影像学、内镜和分子生物学技术等。除传统的X线胸片、磁共振（Magnetic Resonance Imaging,MRI）、正电子发射断层显像（Positron Emission Tomography-Computed Tomography,PET-CT）等方法外,近年来逐步应用的高分辨CT（High-ResolutionComputed Tomography,HRCT）、低剂量CT（Low Dose Computed Tomography,LDCT）、自荧光纤维支气管镜（AutomaticFluorescence Bronchoscopy,AFB）、超声支气管内镜（Endo-Bronchial Ultra-Sound,EBUS）、荧光共聚焦显微镜支气管镜（FiberedConfocal Fluorescence Microscopy,FCFM）、细胞内镜（Endocytoscopy,EC）、电磁导航支气管镜（Electromagnetic NavigationBronchoscopy,ENB）、经支气管针吸活检术（Transbronchial Needle Aspiration,TBNA）、呼出气体分析和肿瘤标记物联合检测等,对于肺癌的早期诊断起到了重要作用,明显改善预后。本文就肺癌早期诊断的研究进展进行综述。     

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC–MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC–MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC–MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.     

Blood biomarker discovery in drug-free schizophrenia: the contribution of proteomics and multiplex immunoassays

Introduction: Recent evidence supports an association between systemic abnormalities and the pathology of psychotic disorders which has led to the search for peripheral blood-based biomarkers.

Areas covered: Here, we summarize blood biomarker findings in schizophrenia from the literature identified by two methods currently driving biomarker discovery in the human proteome; mass spectrometry and multiplex immunoassay. From a total of 14 studies in the serum or plasma of drug-free schizophrenia patients; 47 proteins were found to be significantly altered twice or more, in the same direction. Pathway analysis was performed on these proteins, and the resulting pathways discussed in relation to schizophrenia pathology. Future directions are also discussed, with particular emphasis on the potential for high-throughput validation techniques such as data-independent analysis for confirmation of biomarker candidates.

Expert commentary: We present promising findings that point to a convergence of pathophysiological mechanisms in schizophrenia that involve the acute-phase response, glucocorticoid receptor signalling, coagulation, and lipid and glucose metabolism.     

Mapping and analyzing the human liver proteome: progress and potential

Introduction: The liver is an important organ in humans. Hepatocellular carcinoma (HCC) is one of the deadliest cancers in the world. Progress in the Human Liver Proteome Project (HLPP) has improved understanding of the liver and the liver cancer proteome.

Areas covered: Here, we summarize the recent progress in liver proteome modification profiles, proteomic studies in liver cancer, proteomic study in the search for novel liver cancer biomarkers and drug targets, and progress of the Chromosome Centric Human Proteome Project (CHPP) in the past five years in the Institutes of Biomedical Sciences (IBS) of Fudan University.

Expert commentary: Recent advances and findings discussed here provide great promise of improving the outcome of patients with liver cancer.     

Enzymatic activity of palmitoyl‐protein thioesterase‐1 in serum from schizophrenia significantly associates with schizophrenia diagnosis scales

Genome‐wide association studies have confirmed that schizophrenia is an inheritable multiple‐gene mental disorder. Longitudinal studies about depression, first episode psychosis (FEP) and acute psychotic relapse have mostly searched for brain imaging biomarkers and inflammatory markers from the blood. However, to the best of our knowledge, the association between enzymatic activities with diagnosis or prediction of treatment response in people with schizophrenia has barely been validated. Under the Longitudinal Study of National Mental Health Work Plan (2015‐2020), we have studied a subsample of approximately 36 individuals from the cohort with data on palmitoyl‐protein thioesterase‐1 enzymatic activity from FEP and performed a bivariate correlation analysis with psychiatric assessment scores. After adjusting for sex, age, body mass index (BMI) and total serum protein, our data demonstrated that PPT1 enzymatic activity is significantly associated with schizophrenia and its Positive and Negative Syndrome Scale (PANSS) scores. This longitudinal study compared the PPT1 enzymatic activity in FEP schizophrenia patients and healthy volunteers, and the former exhibited a significant 1.5‐fold increase in PPT1 enzymatic levels (1.79 mmol/L/h/mL, and 1.18 mmol/L/h/mL; P < 0.05; 95% CI, 2.3‐2.9 and 1.4‐1.8). The higher PPT1 enzymatic levels in FEP schizophrenia patients were positively associated with larger PANSS scaling scores (r = 0.32, P = 0.0079 for positive scaling; r = 0.41, P = 0.0006 for negative scaling; r = 0.45, P = 0.0001 for general scaling; and r = 0.34, P = 0.0048 for PNASS‐S scaling). Higher enzymatic PPT1 in FEP schizophrenia patients is significantly associated with increased PANSS scaling values, indicating more serious rates of developing psychosis. Enzymatic activity of PPT1 may provide an important new view for schizophrenia disorders.     

Circulating RNAs as predictive markers for the progression of type 2 diabetes

Type 2 Diabetes Mellitus (T2DM) is the most prevalent form of diabetes in the USA, thus, the identification of biomarkers that could be used to predict the progression from prediabetes to T2DM would be greatly beneficial. Recently, circulating RNA including microRNAs (miRNAs) present in various body fluids have emerged as potential biomarkers for various health conditions, including T2DM. Whereas studies that examine the changes of miRNA spectra between healthy controls and T2DM individuals have been reported, the goal of this study is to conduct a baseline comparison of prediabetic individuals who either progress to T2DM, or remain prediabetic. Using an advanced small RNA sequencing library construction method that improves the detection of miRNA species, we identified 57 miRNAs that showed significant concentration differences between progressors (progress from prediabetes to T2DM) and non‐progressors. Among them, 26 have been previously reported to be associated with T2DM in either body fluids or tissue samples. Some of the miRNAs identified were also affected by obesity. Furthermore, we identified miRNA panels that are able to discriminate progressors from non‐progressors. These results suggest that upon further validation these miRNAs may be useful to predict the risk of conversion to T2DM from prediabetes.