Muscle Fibers Secrete FGFBP1 to Slow Degeneration of Neuromuscular Synapses during Aging and Progression of ALS.

The identity of muscle secreted factors critical for the development and maintenance of neuromuscular junctions (NMJs) remains largely unknown. Here, we show that muscle fibers secrete and concentrate the fibroblast growth factor binding protein 1 (FGFBP1) at NMJs. Although FGFBP1 expression increases during development, its expression decreases before NMJ degeneration during aging and in SOD1G93A mice, a mouse model for amyotrophic lateral sclerosis (ALS). Based on these findings, we examined the impact of deleting FGFBP1 on NMJs. In the absence of FGFBP1, NMJs exhibit structural abnormalities in developing and middle age mice. Deletion of FGFBP1 from SOD1G93A mice also accelerates NMJ degeneration and death. Based on these findings, we sought to identify the mechanism responsible for decreased FGFBP1 in stressed skeletal muscles. We show that FGFBP1 expression is inhibited by increased accumulation of the transforming growth factor-ß1 (TGF-ß1) in skeletal muscles and at their NMJs. These findings suggest that targeting the FGFBP1 and TGF-ß1 signaling axis holds promise for slowing age- and disease-related degeneration of NMJs. SIGNIFICANCE STATEMENT: The neuromuscular junction (NMJ) is critical for all voluntary movement. Its malformation during development and degeneration in adulthood impairs motor function. Therefore, it is important to identify factors that function to maintain the structural integrity of NMJs. We show that muscle fibers secrete and concentrate the fibroblast growth factor binding protein 1 (FGFBP1) at NMJs. However, FGFBP1 expression decreases in skeletal muscles during aging and before NMJ degeneration in SOD1G93A mice, a mouse model for amyotrophic lateral sclerosis. We show that transforming growth factor-ß1 is responsible for the decreased levels of FGFBP1. Importantly, we demonstrate critical roles for FGFBP1 at NMJs in developing, aging and SOD1G93A mice.

Proteomic study reveals a functional network of cancer markers in the G1-Stage of the breast cancer cell cycle.

BACKGROUND: Cancer cells are characterized by a deregulated cell cycle that facilitates abnormal proliferation by allowing cells to by-pass tightly regulated molecular checkpoints such as the G1/S restriction point. To facilitate early diagnosis and the identification of new drug targets, current research efforts focus on studies that could lead to the development of protein panels that collectively can improve the effectiveness of our response to the detection of a life-threatening disease. METHODS: Estrogen-responsive MCF-7 cells were cultured and arrested by serum deprivation in the G1-stage of the cell cycle, and fractionated into nuclear and cytoplasmic fractions. The protein extracts were trypsinized and analyzed by liquid chromatography--mass spectrometry (MS), and the data were interpreted with the Thermo Electron Bioworks software. Biological characterization of the data, selection of cancer markers, and identification of protein interaction networks was accomplished with a combination of bioinformatics tools provided by GoMiner, DAVID and STRING. RESULTS: The objective of this work was to explore via MS proteomic profiling technologies and bioinformatics data mining whether randomly identified cancer markers can be associated with the G1-stage of the cell cycle, i.e., the stage in which cancer cells differ most from normal cells, and whether any functional networks can be identified between these markers and placed in the broader context of cell regulatory pathways. The study enabled the identification of over 2000 proteins and 153 cancer markers, and revealed for the first time that the G1-stage of the cell cycle is not only a rich source of cancer markers, but also a host to an intricate network of functional relationships within the majority of these markers. Three major clusters of interacting proteins emerged: (a) signaling, (b) DNA repair, and (c) oxidative phosphorylation. CONCLUSIONS: The identification of cancer marker regulatory components that act not alone, but within networks, represents an invaluable resource for elucidating the moxlecular mechanisms that govern the uncontrolled proliferation of cancer cells, as well as for catalyzing the development of protein panels with biomarker and drug target potential, screening tests with improved sensitivity and specificity, and novel cancer therapies aimed at pursuing multiple drug targets.

Proteomic snapshot of breast cancer cell cycle: G1/S transition point.

The biological processes that unfold during the G1-phase of the cell cycle are dependent on extracellular mitogenic factors that signal the cell to enter a state of quiescence, or commit to a cell-cycle round by passing the restriction point (R-point) and enter the S-phase. Unlike normal cells, cancer cells evolved the ability to evade the R-point and continue through the cell cycle even in the presence of extensive DNA damage or absence of mitogenic signals. The purpose of this study was to perform a quantitative proteomic evaluation of the biological processes that are responsible for driving MCF-7 breast cancer cells into division even when molecular checkpoints such as the G1/S R-point are in place. Nuclear and cytoplasmic fractions of the G1 and S cell-cycle phases were analyzed by LC-MS/MS to result in the confident identification of more than 2700 proteins. Statistical evaluation of the normalized data resulted in the selection of proteins that displayed twofold or more change in spectral counts in each cell state. Pathway mapping, functional annotation clustering, and protein interaction network analysis revealed that the top-scoring clusters that could play a role in overriding the G1/S transition point included DNA damage response, chromatin remodeling, transcription/translation regulation, and signaling proteins.

Impact of peptide modifications on the isobaric tags for relative and absolute quantitation method accuracy.

In this study, the impact of amino acid modifications on the accuracy of the iTRAQ (isobaric tags for relative and absolute quantitation) method was evaluated. MCF-7 breast cancer cells, cultured in the presence of 17ß-estradiol and tamoxifen, were used as a model system. The cells were labeled and analyzed by reversed-phase liquid chromatography and pulsed Q dissociation ion trap tandem mass spectrometry detection. Database searching was performed by using various combinations of amino acid modification allowances, i.e, Lys/Tyr/Cys and amino terminal iTRAQ labeling, Lys methylation, acetylation and carbamylation, and Cys/Met oxidation. Other than the intended Lys/amino terminal iTRAQ labeling, such modifications occur as a result of either enzymatic or sample preparation related reactions and are typically ignored in quantitation analysis to minimize the rate of false-positive peptide identifications. The study revealed that the modifications with the greatest impact on protein identification and quantitation pertain to Lys and Tyr amino acid residues, that by enabling such modifications the number and type of identified proteins will change (by up to 10%), and that the rate of false-positive protein identifications can be maintained below an upper threshold of 5% if appropriate data filtering conditions are used. In addition, the interference of possible posttranslational modifications (i.e., phosphorylation) with iTRAQ quantitation was examined.

Cell Cycle Model System for Advancing Cancer Biomarker Research.

Progress in understanding the complexity of a devastating disease such as cancer has underscored the need for developing comprehensive panels of molecular markers for early disease detection and precision medicine applications. The present study was conducted to assess whether a cohesive biological context can be assigned to protein markers derived from public data mining, and whether mass spectrometry can be utilized to screen for the co-expression of functionally related biomarkers to be recommended for further exploration in clinical context. Cell cycle arrest/release experiments of MCF7/SKBR3 breast cancer and MCF10 non-tumorigenic cells were used as a surrogate to support the production of proteins relevant to aberrant cell proliferation. Information downloaded from the scientific public domain was queried with bioinformatics tools to generate an initial list of 1038 cancer-associated proteins. Mass spectrometric analysis of cell extracts identified 352 proteins that could be matched to the public list. Differential expression, enrichment, and protein-protein interaction analysis of the proteomic data revealed several functionally-related clusters of relevance to cancer. The results demonstrate that public data derived from independent experiments can be used to inform biological research and support the development of molecular assays for probing the characteristics of a disease.

Loss of CLOCK Results in Dysfunction of Brain Circuits Underlying Focal Epilepsy.

Because molecular mechanisms underlying refractory focal epilepsy are poorly defined, we performed transcriptome analysis on human epileptogenic tissue. Compared with controls, expression of Circadian Locomotor Output Cycles Kaput (CLOCK) is decreased in epileptogenic tissue. To define the function of CLOCK, we generated and tested the Emx-Cre; Clockflox/flox and PV-Cre; Clockflox/flox mouse lines with targeted deletions of the Clock gene in excitatory and parvalbumin (PV)-expressing inhibitory neurons, respectively. The Emx-Cre; Clockflox/flox mouse line alone has decreased seizure thresholds, but no laminar or dendritic defects in the cortex. However, excitatory neurons from the Emx-Cre; Clockflox/flox mouse have spontaneous epileptiform discharges. Both neurons from Emx-Cre; Clockflox/flox mouse and human epileptogenic tissue exhibit decreased spontaneous inhibitory postsynaptic currents. Finally, video-EEG of Emx-Cre; Clockflox/flox mice reveals epileptiform discharges during sleep and also seizures arising from sleep. Altogether, these data show that disruption of CLOCK alters cortical circuits and may lead to generation of focal epilepsy.