Ion Current-Based Proteomic Profiling for Understanding the Inhibitory Effect of Tumor Necrosis Factor Alpha on Myogenic Differentiation.

Despite a demonstrated role for TNF-α in promoting muscle wasting and cachexia, the associated molecular mechanisms and signaling pathways of myoblast differentiation dysregulated by TNF-α remain poorly understood. This study presents well-controlled proteomic profiling as a means to investigate the mechanisms of TNF-α-regulated myogenic differentiation. Primary human muscle precursor cells (MPCs) cultured in growth medium (GM), differentiation medium (DM) to induce myogenic differentiation, and DM with 20 ng/mL of TNF-α (n = 5/group) were comparatively analyzed by an ion current-based quantitative platform consisting of reproducible sample preparation/on-pellet digestion, a long-column nano-LC separation, and ion current-based differential analysis. The inhibition of myogenic differentiation by TNF-α was confirmed by reduced formation of multinucleated myotubes and the recovered expression of altered myogenic proteins such as MYOD and myogenin during myogenic differentiation. Functional analysis and validation by immunoassay analysis suggested that the cooperation of NF-κB and STAT proteins is responsible for dysregulated differentiation in MPCs by TNF-α treatment. Increased MHC class I components such as HLA-A, HLA-B, HLA-C, and beta-2-microglobulin were also observed in cultures in DM treated with TNF-α. Interestingly, inhibition of the cholesterol biosynthesis pathway during myogenic differentiation induced by serum starvation was not recovered by TNF-α treatment, which combined with previous reports, implies that this process may be an early event of myogenesis. This finding could lay the foundation for the potential use of statins in modulating myogenesis through cholesterol, for example, in stem cell-based myocardial infarction treatment, where differentiation of myoblasts and stem cells into force-generating mature muscle cells is a key step to the therapeutic capacity. In conclusion, the landscapes of altered transcription regulators, metabolic processes, and signaling pathways in MPCs are revealed in the regulation of myogenic differentiation by TNF-α, which is valuable for myogenic cellular therapeutics.

Ion-Current-Based Temporal Proteomic Profiling of Influenza-A-Virus-Infected Mouse Lungs Revealed Underlying Mechanisms of Altered Integrity of the Lung Microvascular Barrier.

Investigation of influenza-A-virus (IAV)-infected lung proteomes will greatly promote our understanding on the virus-host crosstalk. Using a detergent-cocktail extraction and digestion procedure and a reproducible ion-current-based method, we performed the first comprehensive temporal analysis of mouse IAV infection. Mouse lung tissues at three time points post-inoculation were compared with controls (n = 4/group), and >1600 proteins were quantified without missing value in any animal. Significantly changed proteins were identified at 4 days (n = 144), 7 days (n = 695), and 10 days (n = 396) after infection, with low false altered protein rates (1.73-8.39%). Functional annotation revealed several key biological processes involved in the systemic host responses. Intriguingly, decreased levels of several cell junction proteins as well as increased levels of tissue metalloproteinase MMP9 were observed, reflecting the IAV-induced structural breakdown of lung epithelial barrier. Supporting evidence of MMP9 activation came from immunoassays examining the abundance and phosphorylation states of all MAPKs and several relevant molecules. Importantly, IAV-induced MMP gelatinase expression was suggested to be specific to MMP9, and p38 MAPK may contribute predominantly to MMP9 elevation. These findings help to resolve the long-lasting debate regarding the signaling pathways of IAV-induced MMP9 expression and shed light on the molecular mechanisms underlying pulmonary capillary-alveolar leak syndrome that can occur during influenza infection.

New Insights into the Disease Progression Control Mechanisms by Comparing Long-Term-Nonprogressors versus Normal-Progressors among HIV-1-Positive Patients Using an Ion Current-Based MS1 Proteomic Profiling.

For decades, epidemiological studies have found significant differences in the susceptibility to disease progression among HIV-carrying patients. One unique group of HIV-1-positive patients, the long-term-nonprogressors (LTNP), exhibits far superior ability in virus control compared with normal-progressors (NP), which proceed to Acquired Immune Deficiency Syndrome (AIDS) much more rapidly. Nonetheless, elucidation of the underlying mechanisms of virus control in LTNP is highly valuable in disease management and treatment but remains poorly understood. Peripheral blood mononuclear cells (PBMC) have been known to play important roles in innate immune responses and thereby would be of great interest for the investigation of the mechanisms of virus defense in LTNP. Here, we described the first comparative proteome analysis of PBMC from LTNP (n = 10) and NP (n = 10) patients using a reproducible ion-current-based MS1 approach, which includes efficient and reproducible sample preparation and chromatographic separation followed by an optimized pipeline for protein identification and quantification. This strategy enables analysis of many biological samples in one set with high quantitative precision and extremely low missing data. In total, 925 unique proteins were quantified under stringent criteria without missing value in any of the 20 subjects, and 87 proteins showed altered expressions between the two patient groups. These proteins are implicated in key processes such as cytoskeleton organization, defense response, apoptosis regulation, intracellular transport, etc., which provided novel insights into the control of disease progressions in LTNP versus NP, and the expression and phosphorylation states of key regulators were further validated by immunoassay. For instance, (1) SAMH1, a potent and "hot" molecule facilitating HIV-1 defense, was for the first time found elevated in LTNP compared with NP or healthy controls; elevated proteins from IFN-α response pathway may also contribute to viral control in LTNP; (2) decreased proapoptotic protein ASC along with the elevation of antiapoptotic proteins may contribute to the less apoptotic profile in PBMC of LTNP; and (3) elevated actin polymerization and less microtubule assembly that impede viral protein transport were first observed in LTNP. These results not only enhanced the understanding of the mechanisms for nonprogression of LTNP, but also may afford highly valuable clues to direct therapeutic efforts. Moreover, this work also demonstrated the ion-current-based MS1 approach as a reliable tool for large-scale clinical research.

Experimental Null Method to Guide the Development of Technical Procedures and to Control False-Positive Discovery in Quantitative Proteomics.

Comprehensive and accurate evaluation of data quality and false-positive biomarker discovery is critical to direct the method development/optimization for quantitative proteomics, which nonetheless remains challenging largely due to the high complexity and unique features of proteomic data. Here we describe an experimental null (EN) method to address this need. Because the method experimentally measures the null distribution (either technical or biological replicates) using the same proteomic samples, the same procedures and the same batch as the case-vs-contol experiment, it correctly reflects the collective effects of technical variability (e.g., variation/bias in sample preparation, LC-MS analysis, and data processing) and project-specific features (e.g., characteristics of the proteome and biological variation) on the performances of quantitative analysis. To show a proof of concept, we employed the EN method to assess the quantitative accuracy and precision and the ability to quantify subtle ratio changes between groups using different experimental and data-processing approaches and in various cellular and tissue proteomes. It was found that choices of quantitative features, sample size, experimental design, data-processing strategies, and quality of chromatographic separation can profoundly affect quantitative precision and accuracy of label-free quantification. The EN method was also demonstrated as a practical tool to determine the optimal experimental parameters and rational ratio cutoff for reliable protein quantification in specific proteomic experiments, for example, to identify the necessary number of technical/biological replicates per group that affords sufficient power for discovery. Furthermore, we assessed the ability of EN method to estimate levels of false-positives in the discovery of altered proteins, using two concocted sample sets mimicking proteomic profiling using technical and biological replicates, respectively, where the true-positives/negatives are known and span a wide concentration range. It was observed that the EN method correctly reflects the null distribution in a proteomic system and accurately measures false altered proteins discovery rate (FADR). In summary, the EN method provides a straightforward, practical, and accurate alternative to statistics-based approaches for the development and evaluation of proteomic experiments and can be universally adapted to various types of quantitative techniques.