Robust Detection of Hierarchical Communities from Escherichia coli Gene Expression Data

Determining the functional structure of biological networks is a central goal of systems biology. One approach is to analyze gene expression data to infer a network of gene interactions on the basis of their correlated responses to environmental and genetic perturbations. The inferred network can then be analyzed to identify functional communities. However, commonly used algorithms can yield unreliable results due to experimental noise, algorithmic stochasticity, and the influence of arbitrarily chosen parameter values. Furthermore, the results obtained typically provide only a simplistic view of the network partitioned into disjoint communities and provide no information of the relationship between communities. Here, we present methods to robustly detect coregulated and functionally enriched gene communities and demonstrate their application and validity for Escherichia coli gene expression data. Applying a recently developed community detection algorithm to the network of interactions identified with the context likelihood of relatedness (CLR) method, we show that a hierarchy of network communities can be identified. These communities significantly enrich for gene ontology (GO) terms, consistent with them representing biologically meaningful groups. Further, analysis of the most significantly enriched communities identified several candidate new regulatory interactions. The robustness of our methods is demonstrated by showing that a core set of functional communities is reliably found when artificial noise, modeling experimental noise, is added to the data. We find that noise mainly acts conservatively, increasing the relatedness required for a network link to be reliably assigned and decreasing the size of the core communities, rather than causing association of genes into new communities.Comment: Due to appear in PLoS Computational Biology. Supplementary Figure S1 was not uploaded but is available by contacting the author. 27 pages, 5 figures, 15 supplementary file

Cytoplasmic p53 couples oncogene-driven glucose metabolism to apoptosis and is a therapeutic target in glioblastoma.

Cross-talk among oncogenic signaling and metabolic pathways may create opportunities for new therapeutic strategies in cancer. Here we show that although acute inhibition of EGFR-driven glucose metabolism induces only minimal cell death, it lowers the apoptotic threshold in a subset of patient-derived glioblastoma (GBM) cells. Mechanistic studies revealed that after attenuated glucose consumption, Bcl-xL blocks cytoplasmic p53 from triggering intrinsic apoptosis. Consequently, targeting of EGFR-driven glucose metabolism in combination with pharmacological stabilization of p53 with the brain-penetrant small molecule idasanutlin resulted in synthetic lethality in orthotopic glioblastoma xenograft models. Notably, neither the degree of EGFR-signaling inhibition nor genetic analysis of EGFR was sufficient to predict sensitivity to this therapeutic combination. However, detection of rapid inhibitory effects on [18F]fluorodeoxyglucose uptake, assessed through noninvasive positron emission tomography, was an effective predictive biomarker of response in vivo. Together, these studies identify a crucial link among oncogene signaling, glucose metabolism, and cytoplasmic p53, which may potentially be exploited for combination therapy in GBM and possibly other malignancies

CRISPR-Cas9 screens in human cells and primary neurons identify modifiers of C9ORF72 dipeptide-repeat-protein toxicity.

Hexanucleotide-repeat expansions in the C9ORF72 gene are the most common cause of amyotrophic lateral sclerosis and frontotemporal dementia (c9ALS/FTD). The nucleotide-repeat expansions are translated into dipeptide-repeat (DPR) proteins, which are aggregation prone and may contribute to neurodegeneration. We used the CRISPR-Cas9 system to perform genome-wide gene-knockout screens for suppressors and enhancers of C9ORF72 DPR toxicity in human cells. We validated hits by performing secondary CRISPR-Cas9 screens in primary mouse neurons. We uncovered potent modifiers of DPR toxicity whose gene products function in nucleocytoplasmic transport, the endoplasmic reticulum (ER), proteasome, RNA-processing pathways, and chromatin modification. One modifier, TMX2, modulated the ER-stress signature elicited by C9ORF72 DPRs in neurons and improved survival of human induced motor neurons from patients with C9ORF72 ALS. Together, our results demonstrate the promise of CRISPR-Cas9 screens in defining mechanisms of neurodegenerative diseases

Cost of managing an episode of relapse in multiple sclerosis in the United States

BACKGROUND: The purpose of this study was to determine the direct medical US cost of managing multiple sclerosis relapses. METHODS: Direct data analysis and cost modeling were employed to derive typical resource use profiles and costs in 2002 US dollars, from the perspective of a third-party payer responsible for comprehensive health-care. The location and scope of health care services provided over a 90-day period were used to define three levels of relapse management. Hospitalization and resulting subsequent care was defined as high intensity management. A medium level of intervention was defined as either use of the emergency room, an observational unit, or administration of acute treatments, such as intravenous methylprednisolone in an outpatient or home setting. The lowest intensity of care comprised physician office visits and symptom-related medications. Data were obtained from many sources including all payer inpatient, ambulatory and emergency room databases from several states, fee schedules, government reports, and literature. All charges were adjusted using cost-to-charge ratios. RESULTS: Average cost per person for high management level was $12,870, based on analysis of 4,634 hospital cases (mean age 48 years, 73$1,847 and mild episode $243. CONCLUSIONS: Management strategies leading to a reduction in the frequency and severity of a relapse, less reliance on inpatient care, or increased access to steroid infusions in the home, would have a substantial impact on the economic consequences of managing relapses

Appropriate criteria for identification of near-miss maternal morbidity in tertiary care facilities: A cross sectional study

<p>Abstract</p> <p>Background</p> <p>The study of severe maternal morbidity survivors (near miss) may be an alternative or a complement to the study of maternal death events as a health care indicator. However, there is still controversy regarding the criteria for identification of near-miss maternal morbidity. This study aimed to characterize the near miss maternal morbidity according to different sets of criteria.</p> <p>Methods</p> <p>A descriptive study in a tertiary center including 2,929 women who delivered there between July 2003 and June 2004. Possible cases of near miss were daily screened by checking different sets of criteria proposed elsewhere. The main outcome measures were: rate of near miss and its primary determinant factors, criteria for its identification, total hospital stay, ICU stay, and number and kind of special procedures performed.</p> <p>Results</p> <p>There were two maternal deaths and 124 cases of near miss were identified, with 102 of them admitted to the ICU (80.9%). Among the 126 special procedures performed, the most frequent were central venous access, echocardiography and invasive mechanical ventilation. The mean hospital stay was 10.3 (± 13.24) days. Hospital stay and the number of special procedures performed were significantly higher when the organ dysfunction based criteria were applied.</p> <p>Conclusion</p> <p>The adoption of a two level screening strategy may lead to the development of a consistent severe maternal morbidity surveillance system but further research is needed before worldwide near miss criteria can be assumed.</p

Rac Inhibition Reverses the Phenotype of Fibrotic Fibroblasts

Background: Fibrosis, the excessive deposition of scar tissue by fibroblasts, is one of the largest groups of diseases for which there is no therapy. Fibroblasts from lesional areas of scleroderma patients possess elevated abilities to contract matrix and produce alpha-smooth muscle actin (alpha-SMA), type I collagen and CCN2 (connective tissue growth factor, CTGF). The basis for this phenomenon is poorly understood, and is a necessary prerequisite for developing novel, rational anti-fibrotic strategies.Methods and Findings: Compared to healthy skin fibroblasts, dermal fibroblasts cultured from lesional areas of scleroderma (SSc) patients possess elevated Rac activity. NSC23766, a Rac inhibitor, suppressed the persistent fibrotic phenotype of lesional SSc fibroblasts. NSC23766 caused a decrease in migration on and contraction of matrix, and alpha-SMA, type I collagen and CCN2 mRNA and protein expression. SSc fibroblasts possessed elevated Akt phosphorylation, which was also blocked by NSC23766. Overexpression of rac1 in normal fibroblasts induced matrix contraction and alpha-SMA, type I collagen and CCN2 mRNA and protein expression. Rac1 activity was blocked by PI3kinase/Akt inhibition. Basal fibroblast activity was not affected by NSC23766.Conclusion: Rac inhibition may be considered as a novel treatment for the fibrosis observed in SSc

An HR-MAS MR Metabolomics Study on Breast Tissues Obtained with Core Needle Biopsy

BACKGROUND: Much research has been devoted to the development of new breast cancer diagnostic measures, including those involving high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopic techniques. Previous HR-MAS MR results have been obtained from post-surgery samples, which limits their direct clinical applicability. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we performed HR-MAS MR spectroscopic studies on 31 breast tissue samples (13 cancer and 18 non-cancer) obtained by percutaneous core needle biopsy. We showed that cancer and non-cancer samples can be discriminated very well with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA) multivariate model on the MR spectra. A subsequent blind test showed 69% sensitivity and 94% specificity in the prediction of the cancer status. A spectral analysis showed that in cancer cells, taurine- and choline-containing compounds are elevated. Our approach, additionally, could predict the progesterone receptor statuses of the cancer patients. CONCLUSIONS/SIGNIFICANCE: HR-MAS MR metabolomics on intact breast tissues obtained by core needle biopsy may have a potential to be used as a complement to the current diagnostic and prognostic measures for breast cancers

HypertenGene: extracting key hypertension genes from biomedical literature with position and automatically-generated template features

<p>Abstract</p> <p>Background</p> <p>The genetic factors leading to hypertension have been extensively studied, and large numbers of research papers have been published on the subject. One of hypertension researchers' primary research tasks is to locate key hypertension-related genes in abstracts. However, gathering such information with existing tools is not easy: (1) Searching for articles often returns far too many hits to browse through. (2) The search results do not highlight the hypertension-related genes discovered in the abstract. (3) Even though some text mining services mark up gene names in the abstract, the key genes investigated in a paper are still not distinguished from other genes. To facilitate the information gathering process for hypertension researchers, one solution would be to extract the key hypertension-related genes in each abstract. Three major tasks are involved in the construction of this system: (1) gene and hypertension named entity recognition, (2) section categorization, and (3) gene-hypertension relation extraction.</p> <p>Results</p> <p>We first compare the retrieval performance achieved by individually adding template features and position features to the baseline system. Then, the combination of both is examined. We found that using position features can almost double the original AUC score (0.8140vs.0.4936) of the baseline system. However, adding template features only results in marginal improvement (0.0197). Including both improves AUC to 0.8184, indicating that these two sets of features are complementary, and do not have overlapping effects. We then examine the performance in a different domain--diabetes, and the result shows a satisfactory AUC of 0.83.</p> <p>Conclusion</p> <p>Our approach successfully exploits template features to recognize true hypertension-related gene mentions and position features to distinguish key genes from other related genes. Templates are automatically generated and checked by biologists to minimize labor costs. Our approach integrates the advantages of machine learning models and pattern matching. To the best of our knowledge, this the first systematic study of extracting hypertension-related genes and the first attempt to create a hypertension-gene relation corpus based on the GAD database. Furthermore, our paper proposes and tests novel features for extracting key hypertension genes, such as relative position, section, and template features, which could also be applied to key-gene extraction for other diseases.</p

Acute Response of Peripheral Blood Cell to Autologous Hematopoietic Stem Cell Transplantation in Type 1 Diabetic Patient

Autologous nonmyeloablative hematopoietic stem cell transplantation (AHST) was the first therapeutic approach that can improve β cell function in type 1 diabetic (T1D) patients. This study was designed to investigate the potential mechanisms involved.We applied AHST to nine T1D patients diagnosed within six months and analyzed the acute responses in peripheral blood for lymphocyte subpopulation as well as for genomic expression profiling at the six-month follow-up.We found six patients obtained insulin free (IF group) and three remained insulin dependent (ID group); C-peptide production was significantly higher in IF group compared to ID group. The acute responses in lymphocytes at six-month follow-up include declined CD3(+)CD4(+), CD3(+)CD8(+) T cell population and recovered B cell, NK cell population in both groups but with no significant differences between the two groups; most immune-related genes and pathways were up-regulated in peripheral blood mononuclear cell (PBMC) of both groups while none of transcription factors for immune regulatory component were significantly changed; the IF group demonstrated more AHST-modified genetic events than the ID group and distinct pattern of top pathways, co-expression network as well as 'hub' genes (eg, TCF7 and GZMA) were associated with each group.AHST could improve the islet function in newly diagnosed T1D patients and elimination of the islet specific autoreactive T cells might be one of the mechanisms involved; T1D patients responded differently to AHST possibly due to the distinct transcriptional events occurring in PBMC.ClinicalTrials.gov NCT00807651

Lack of Wdr13 Gene in Mice Leads to Enhanced Pancreatic Beta Cell Proliferation, Hyperinsulinemia and Mild Obesity

WD-repeat proteins are very diverse, yet these are structurally related proteins that participate in a wide range of cellular functions. WDR13, a member of this family, is conserved from fishes to humans and localizes into the nucleus. To understand the in vivo function(s) of Wdr13 gene, we have created and characterized a mutant mouse strain lacking this gene. The mutant mice had higher serum insulin levels and increased pancreatic islet mass as a result of enhanced beta cell proliferation. While a known cell cycle inhibitor, p21, was downregulated in the mutant islets, over expression of WDR13 in the pancreatic beta cell line (MIN6) resulted in upregulation of p21, accompanied by retardation of cell proliferation. We suggest that WDR13 is a novel negative regulator of the pancreatic beta cell proliferation. Given the higher insulin levels and better glucose clearance in Wdr13 gene deficient mice, we propose that this protein may be a potential candidate drug target for ameliorating impaired glucose metabolism in diabetes