Differential regulation of Krüppel-like factor family transcription factor expression in neonatal rat cardiac myocytes: effects of endothelin-1, oxidative stress and cytokines

Krüppel-like transcription factors (Klfs) modulate fundamental cell processes. Cardiac myocytes are terminally-differentiated, but hypertrophy in response to stimuli such as endothelin-1. H2O2 or cytokines promote myocyte apoptosis. Microarray studies of neonatal rat myocytes identified several Klfs as endothelin-1-responsive genes. We used quantitative PCR for further analysis of Klf expression in neonatal rat myocytes. In response to endothelin-1, Klf2 mRNA expression was rapidly increased ( approximately 9-fold; 15-30 min) with later increases in expression of Klf4 and Klf6 ( approximately 5-fold; 30-60 min). All were regulated as immediate early genes (cycloheximide did not inhibit the increases in expression). Klf5 expression was increased at 1-2 h ( approximately 13-fold) as a second phase response (cycloheximide inhibited the increase). These increases were transient and attenuated by U0126. H2O2 increased expression of Klf2, Klf4 and Klf6, but interleukin-1beta or tumor necrosis factor alpha downregulated Klf2 expression with no effect on Klf4 or Klf6. Of the Klfs which repress transcription, endothelin-1 rapidly downregulated expression of Klf3, Klf11 and Klf15. The dynamic regulation of expression of multiple Klf family members in cardiac myocytes suggests that, as a family, they are actively involved in regulating phenotypic responses (hypertrophy and apoptosis) to extracellular stimuli

Testing for differential abundance in mass cytometry data.

When comparing biological conditions using mass cytometry data, a key challenge is to identify cellular populations that change in abundance. Here, we present a computational strategy for detecting 'differentially abundant' populations by assigning cells to hyperspheres, testing for significant differences between conditions and controlling the spatial false discovery rate. Our method (http://bioconductor.org/packages/cydar) outperforms other approaches in simulations and finds novel patterns of differential abundance in real data.This work was supported by Cancer Research UK (core funding to J.C.M., award no. A17197), the University of Cambridge and Hutchison Whampoa Limited. J.C.M. was also supported by core funding from EMBL

Modeling flow cytometry data for cancer vaccine immune monitoring

Flow cytometry (FCM) is widely used in cancer research for diagnosis, detection of minimal residual disease, as well as immune monitoring and profiling following immunotherapy. In all these applications, the challenge is to detect extremely rare cell subsets while avoiding spurious positive events. To achieve this objective, it helps to be able to analyze FCM data using multiple markers simultaneously, since the additional information provided often helps to minimize the number of false positive and false negative events, hence increasing both sensitivity and specificity. However, with manual gating, at most two markers can be examined in a single dot plot, and a sequential strategy is often used. As the sequential strategy discards events that fall outside preceding gates at each stage, the effectiveness of the strategy is difficult to evaluate without laborious and painstaking back-gating. Model-based analysis is a promising computational technique that works using information from all marker dimensions simultaneously, and offers an alternative approach to flow analysis that can usefully complement manual gating in the design of optimal gating strategies. Results from model-based analysis will be illustrated with examples from FCM assays commonly used in cancer immunotherapy laboratories

An integrative paradigm to impart quality to correlative science

Correlative studies are a primary mechanism through which insights can be obtained about the bioactivity and potential efficacy of candidate therapeutics evaluated in early-stage clinical trials. Accordingly, well designed and performed early-stage correlative studies have the potential to strongly influence further clinical development of candidate therapeutic agents, and correlative data obtained from early stage trials has the potential to provide important guidance on the design and ultimate successful evaluation of products in later stage trials, particularly in the context of emerging clinical trial paradigms such as adaptive trial design

Large-scale mapping of human protein–protein interactions by mass spectrometry

Mapping protein–protein interactions is an invaluable tool for understanding protein function. Here, we report the first large-scale study of protein–protein interactions in human cells using a mass spectrometry-based approach. The study maps protein interactions for 338 bait proteins that were selected based on known or suspected disease and functional associations. Large-scale immunoprecipitation of Flag-tagged versions of these proteins followed by LC-ESI-MS/MS analysis resulted in the identification of 24 540 potential protein interactions. False positives and redundant hits were filtered out using empirical criteria and a calculated interaction confidence score, producing a data set of 6463 interactions between 2235 distinct proteins. This data set was further cross-validated using previously published and predicted human protein interactions. In-depth mining of the data set shows that it represents a valuable source of novel protein–protein interactions with relevance to human diseases. In addition, via our preliminary analysis, we report many novel protein interactions and pathway associations

Exercise training with dietary counselling increases mitochondrial chaperone expression in middle-aged subjects with impaired glucose tolerance

<p>Abstract</p> <p>Background</p> <p>Insulin resistance and diabetes are associated with increased oxidative stress and impairment of cellular defence systems. Our purpose was to investigate the interaction between glucose metabolism, antioxidative capacity and heat shock protein (HSP) defence in different skeletal muscle phenotypes among middle-aged obese subjects during a long-term exercise and dietary intervention. As a sub-study of the Finnish Diabetes Prevention Study (DPS), 22 persons with impaired glucose tolerance (IGT) taking part in the intervention volunteered to give samples from the <it>vastus lateralis </it>muscle. Subjects were divided into two sub-groups (IGTslow and IGTfast) on the basis of their baseline myosin heavy chain profile. Glucose metabolism, oxidative stress and HSP expressions were measured before and after the 2-year intervention.</p> <p>Results</p> <p>Exercise training, combined with dietary counselling, increased the expression of mitochondrial chaperones HSP60 and glucose-regulated protein 75 (GRP75) in the <it>vastus lateralis </it>muscle in the IGTslow group and that of HSP60 in the IGTfast group. In cytoplasmic chaperones HSP72 or HSP90 no changes took place. In the IGTslow group, a significant positive correlation between the increased muscle content of HSP60 and the oxygen radical absorbing capacity values and, in the IGTfast group, between the improved VO_2maxvalue and the increased protein expression of GRP75 were found. Serum uric acid concentrations decreased in both sub-groups and serum protein carbonyl concentrations decreased in the IGTfast group.</p> <p>Conclusion</p> <p>The 2-year intervention up-regulated mitochondrial HSP expressions in middle-aged subjects with impaired glucose tolerance. These improvements, however, were not correlated directly with enhanced glucose tolerance.</p

Vertebrate Paralogous MEF2 Genes: Origin, Conservation, and Evolution

BACKGROUND: The myocyte enhancer factor 2 (MEF2) gene family is broadly expressed during the development and maintenance of muscle cells. Although a great deal has been elucidated concerning MEF2 transcription factors' regulation of specific gene expression in diverse programs and adaptive responses, little is known about the origin and evolution of the four members of the MEF2 gene family in vertebrates. METHODOLOGY/PRINCIPAL FINDINGS: By phylogenetic analyses, we investigated the origin, conservation, and evolution of the four MEF2 genes. First, among the four MEF2 paralogous branches, MEF2B is clearly distant from the other three branches in vertebrates, mainly because it lacks the HJURP_C (Holliday junction recognition protein C-terminal) region. Second, three duplication events might have occurred to produce the four MEF2 paralogous genes and the latest duplication event occurred near the origin of vertebrates producing MEF2A and MEF2C. Third, the ratio (K(a)/K(s)) of non-synonymous to synonymous nucleotide substitution rates showed that MEF2B evolves faster than the other three MEF2 proteins despite purifying selection on all of the four MEF2 branches. Moreover, a pair model of M0 versus M3 showed that variable selection exists among MEF2 proteins, and branch-site analysis presented that sites 53 and 64 along the MEF2B branch are under positive selection. Finally, and interestingly, substitution rates showed that type II MADS genes (i.e., MEF2-like genes) evolve as slowly as type I MADS genes (i.e., SRF-like genes) in animals, which is inconsistent with the fact that type II MADS genes evolve much slower than type I MADS genes in plants. CONCLUSION: Our findings shed light on the relationship of MEF2A, B, C, and D with functional conservation and evolution in vertebrates. This study provides a rationale for future experimental design to investigate distinct but overlapping regulatory roles of the four MEF2 genes in various tissues

Biomarkers in T cell therapy clinical trials

T cell therapy represents an emerging and promising modality for the treatment of both infectious disease and cancer. Data from recent clinical trials have highlighted the potential for this therapeutic modality to effect potent anti-tumor activity. Biomarkers, operationally defined as biological parameters measured from patients that provide information about treatment impact, play a central role in the development of novel therapeutic agents. In the absence of information about primary clinical endpoints, biomarkers can provide critical insights that allow investigators to guide the clinical development of the candidate product. In the context of cell therapy trials, the definition of biomarkers can be extended to include a description of parameters of the cell product that are important for product bioactivity

A dynamic role for HDAC7 in MEF2-mediated muscle differentiation

The overlapping expression profile of MEF2 and the class-II histone deacetylase, HDAC7, led us to investigate the functional interaction and relationship between these regulatory proteins. HDAC7 expression inhibits the activity of MEF2 (-A, -C, and -D), and in contrast MyoD and Myogenin activities are not affected. Glutathione S-transferase pulldown and immunoprecipitation demonstrate that the repression mechanism involves direct interactions between MEF2 proteins and HDAC7 and is associated with the ability of MEF2 to interact with the N-terminal 121 amino acids of HDAC7 that encode repression domain 1. The MADS domain of MEF2 mediates the direct interaction of MEF2 with HDAC7, MEF2 inhibition by HDAC7 is dependent on the N-terminal repression domain and surprisingly does not involve the C-terminal deacetylase domain. HDAC7 interacts with CtBP and other class-I and -II HDACs suggesting that silencing of MEF2 activity involves corepressor recruitment. Furthermore, we show that induction of muscle differentiation by serum withdrawal leads to the translocation of HDAC7 from the nucleus into the cytoplasm. This work demonstrates that HDAC7 regulates the function of MEF2 proteins and suggests that this class-II HDAC regulates this important transcriptional (and pathophysiological) target in heart and muscle tissue. The nucleocytoplasmic trafficking of HDAC7 and other class-II HDACs during myogenesis provides an ideal mechanism for the regulation of HDAC targets during mammalian development and differentiation