A Minimal Threshold of c-di-GMP Is Essential for Fruiting Body Formation and Sporulation in Myxococcus xanthus

Generally, the second messenger bis-(3’-5’)-cyclic dimeric GMP (c-di-GMP) regulates the switch between motile and sessile lifestyles in bacteria. Here, we show that c-di-GMP is an essential regulator of multicellular development in the social bacterium Myxococcus xanthus. In response to starvation, M. xanthus initiates a developmental program that culminates in formation of spore-filled fruiting bodies. We show that c-di-GMP accumulates at elevated levels during development and that this increase is essential for completion of development whereas excess c-di-GMP does not interfere with development. MXAN3735 (renamed DmxB) is identified as a diguanylate cyclase that only functions during development and is responsible for this increased c-di-GMP accumulation. DmxB synthesis is induced in response to starvation, thereby restricting DmxB activity to development. DmxB is essential for development and functions downstream of the Dif chemosensory system to stimulate exopolysaccharide accumulation by inducing transcription of a subset of the genes encoding proteins involved in exopolysaccharide synthesis. The developmental defects in the dmxB mutant are non-cell autonomous and rescued by co-development with a strain proficient in exopolysaccharide synthesis, suggesting reduced exopolysaccharide accumulation as the causative defect in this mutant. The NtrC-like transcriptional regulator EpsI/Nla24, which is required for exopolysaccharide accumulation, is identified as a c-diGMP receptor, and thus a putative target for DmxB generated c-di-GMP. Because DmxB can be—at least partially—functionally replaced by a heterologous diguanylate cyclase, these results altogether suggest a model in which a minimum threshold level of c-di-GMP is essential for the successful completion of multicellular development in M. xanthus

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

<p>Abstract</p> <p>Background</p> <p>The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions.</p> <p>Results</p> <p>In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification.</p> <p>Conclusion</p> <p>High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.</p

Query Large Scale Microarray Compendium Datasets Using a Model-Based Bayesian Approach with Variable Selection

In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors

Supervised group Lasso with applications to microarray data analysis

BACKGROUND: A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. RESULTS: We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. CONCLUSION: We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods

Vignette studies of medical choice and judgement to study caregivers' medical decision behaviour: systematic review

BACKGROUND: Vignette studies of medical choice and judgement have gained popularity in the medical literature. Originally developed in mathematical psychology they can be used to evaluate physicians' behaviour in the setting of diagnostic testing or treatment decisions. We provide an overview of the use, objectives and methodology of these studies in the medical field. METHODS: Systematic review. We searched in electronic databases; reference lists of included studies. We included studies that examined medical decisions of physicians, nurses or medical students using cue weightings from answers to structured vignettes. Two reviewers scrutinized abstracts and examined full text copies of potentially eligible studies. The aim of the included studies, the type of clinical decision, the number of participants, some technical aspects, and the type of statistical analysis were extracted in duplicate and discrepancies were resolved by consensus. RESULTS: 30 reports published between 1983 and 2005 fulfilled the inclusion criteria. 22 studies (73%) reported on treatment decisions and 27 (90%) explored the variation of decisions among experts. Nine studies (30%) described differences in decisions between groups of caregivers and ten studies (33%) described the decision behaviour of only one group. Only six studies (20%) compared decision behaviour against an empirical reference of a correct decision. The median number of considered attributes was 6.5 (IQR 4-9), the median number of vignettes was 27 (IQR 16-40). In 17 studies, decision makers had to rate the relative importance of a given vignette; in six studies they had to assign a probability to each vignette. Only ten studies (33%) applied a statistical procedure to account for correlated data. CONCLUSION: Various studies of medical choice and judgement have been performed to depict weightings of the value of clinical information from answers to structured vignettes of care givers. We found that the design and analysis methods used in current applications vary considerably and could be improved in a large number of cases

Problems of multi-species organisms: endosymbionts to holobionts

The organism is one of the fundamental concepts of biology and has been at the center of many discussions about biological individuality, yet what exactly it is can be confusing. The definition that we find generally useful is that an organism is a unit in which all the subunits have evolved to be highly cooperative, with very little conflict. We focus on how often organisms evolve from two or more formerly independent organisms. Two canonical transitions of this type—replicators clustered in cells and endosymbiotic organelles within host cells—demonstrate the reality of this kind of evolutionary transition and suggest conditions that can favor it. These conditions include co-transmission of the partners across generations and rules that strongly regulate and limit conflict, such as a fair meiosis. Recently, much attention has been given to associations of animals with microbes involved in their nutrition. These range from tight endosymbiotic associations like those between aphids and Buchnera bacteria, to the complex communities in animal intestines. Here, starting with a reflection about identity through time (which we call “Theseus’s fish”), we consider the distinctions between these kinds of animal–bacteria interactions and describe the criteria by which a few can be considered jointly organismal but most cannot

Mycobacterium tuberculosis Rv3586 (DacA) Is a Diadenylate Cyclase That Converts ATP or ADP into c-di-AMP

Cyclic diguanosine monophosphate (c-di-GMP) and cyclic diadenosine monophosphate (c-di-AMP) are recently identified signaling molecules. c-di-GMP has been shown to play important roles in bacterial pathogenesis, whereas information about c-di-AMP remains very limited. Mycobacterium tuberculosis Rv3586 (DacA), which is an ortholog of Bacillus subtilis DisA, is a putative diadenylate cyclase. In this study, we determined the enzymatic activity of DacA in vitro using high-performance liquid chromatography (HPLC), mass spectrometry (MS) and thin layer chromatography (TLC). Our results showed that DacA was mainly a diadenylate cyclase, which resembles DisA. In addition, DacA also exhibited residual ATPase and ADPase in vitro. Among the potential substrates tested, DacA was able to utilize both ATP and ADP, but not AMP, pApA, c-di-AMP or GTP. By using gel filtration and analytical ultracentrifugation, we further demonstrated that DacA existed as an octamer, with the N-terminal domain contributing to tetramerization and the C-terminal domain providing additional dimerization. Both the N-terminal and the C-terminal domains were essential for the DacA's enzymatically active conformation. The diadenylate cyclase activity of DacA was dependent on divalent metal ions such as Mg2+, Mn2+ or Co2+. DacA was more active at a basic pH rather than at an acidic pH. The conserved RHR motif in DacA was essential for interacting with ATP, and mutation of this motif to AAA completely abolished DacA's diadenylate cyclase activity. These results provide the molecular basis for designating DacA as a diadenylate cyclase. Our future studies will explore the biological function of this enzyme in M. tuberculosis

A higher activation threshold of memory CD8+ T cells has a fitness cost that is modified by TCR affinity during Tuberculosis

All relevant data are within the paper and its Supporting Information files except for the primary TCR sequences. The data files for the primary TCR sequences are publicly deposited in the University of Massachusetts Medical School’s institutional repository, eScholarship@UMMS. The permanent link to the data is http://dx.doi.org/10.13028/M2CC70T cell vaccines against Mycobacterium tuberculosis (Mtb) and other pathogens are based on the principle that memory T cells rapidly generate effector responses upon challenge, leading to pathogen clearance. Despite eliciting a robust memory CD8+ T cell response to the immunodominant Mtb antigen TB10.4 (EsxH), we find the increased frequency of TB10.4-specific CD8+ T cells conferred by vaccination to be short-lived after Mtb challenge. To compare memory and naïve CD8+ T cell function during their response to Mtb, we track their expansions using TB10.4-specific retrogenic CD8+ T cells. We find that the primary (naïve) response outnumbers the secondary (memory) response during Mtb challenge, an effect moderated by increased TCR affinity. To determine whether the expansion of polyclonal memory T cells is restrained following Mtb challenge, we used TCRβ deep sequencing to track TB10.4-specific CD8+ T cells after vaccination and subsequent challenge in intact mice. Successful memory T cells, defined by their clonal expansion after Mtb challenge, express similar CDR3β sequences suggesting TCR selection by antigen. Thus, both TCR-dependent and -independent factors affect the fitness of memory CD8+ responses. The impaired expansion of the majority of memory T cell clonotypes may explain why some TB vaccines have not provided better protection.This work was supported by NIH R01 AI106725 as well as fellowship funding to SC from NIH AI T32 007061 and the UMass GSBS Millennium Program. The Small Animal Biocontainment Suite was supported in part by Center for AIDS Research Grant P30 AI 060354. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

HuR/ELAVL1 drives malignant peripheral nerve sheath tumor growth and metastasis

Cancer cells can develop a strong addiction to discrete molecular regulators, which control the aberrant gene expression programs that drive and maintain the cancer phenotype. Here, we report the identification of the RNA-binding protein HuR/ELAVL1 as a central oncogenic driver for malignant peripheral nerve sheath tumors (MPNSTs), which are highly aggressive sarcomas that originate from cells of the Schwann cell lineage. HuR was found to be highly elevated and bound to a multitude of cancer-associated transcripts in human MPNST samples. Accordingly, genetic and pharmacological inhibition of HuR had potent cytostatic and cytotoxic effects on tumor growth, and strongly suppressed metastatic capacity in vivo. Importantly, we linked the profound tumorigenic function of HuR to its ability to simultaneously regulate multiple essential oncogenic pathways in MPNST cells, including the Wnt/β-catenin, YAP/TAZ, RB/E2F, and BET pathways, which converge on key transcriptional networks. Given the exceptional dependency of MPNST cells on HuR for survival, proliferation, and dissemination, we propose that HuR represents a promising therapeutic target for MPNST treatment

Induction of Cytoplasmic Rods and Rings Structures by Inhibition of the CTP and GTP Synthetic Pathway in Mammalian Cells

Background: Cytoplasmic filamentous rods and rings (RR) structures were identified using human autoantibodies as probes. In the present study, the formation of these conserved structures in mammalian cells and functions linked to these structures were examined. Methodology/Principal Findings: Distinct cytoplasmic rods (,3–10 mm in length) and rings (,2–5 mm in diameter) in HEp-2 cells were initially observed in immunofluorescence using human autoantibodies. Co-localization studies revealed that, although RR had filament-like features, they were not enriched in actin, tubulin, or vimentin, and not associated with centrosomes or other known cytoplasmic structures. Further independent studies revealed that two key enzymes in the nucleotide synthetic pathway cytidine triphosphate synthase 1 (CTPS1) and inosine monophosphate dehydrogenase 2 (IMPDH2) were highly enriched in RR. CTPS1 enzyme inhibitors 6-diazo-5-oxo-L-norleucine and Acivicin as well as the IMPDH2 inhibitor Ribavirin exhibited dose-dependent induction of RR in.95 % of cells in all cancer cell lines tested as well as mouse primary cells. RR formation by lower concentration of Ribavirin was enhanced in IMPDH2-knockdown HeLa cells whereas it was inhibited in GFP-IMPDH2 overexpressed HeLa cells. Interestingly, RR were detected readily in untreated mouse embryonic stem cells (.95%); upon retinoic acid differentiation, RR disassembled in these cells but reformed when treated with Acivicin