Unscented Kalman filter with parameter identifiability analysis for the estimation of multiple parameters in kinetic models

In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF), rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison

Suppression of zinc finger protein 467 alleviates osteoporosis through promoting differentiation of adipose derived stem cells to osteoblasts

Osteoblast and adipocyte are derived from common mesenchymal progenitor cells. The bone loss of osteoporosis is associated with altered progenitor differentiation from an osteoblastic to an adipocytic lineage. In this study, a comparative analysis of gene expression profiling using cDNA microarray and realtime-PCR indicated that Zinc finger protein 467 (Zfp467) involved in adipocyte and osteoblast differentiation of cultured adipose derived stem cells (ADSCs). Our results showed that RNA interference for Zfp467 in ADSCs inhibited adipocyte formation and stimulated osteoblast commitment. The mRNA levels of osteogenic and adipogenic markers in ADSCs were regulated by si-Zfp467. Zfp467 RNAi in ADSCs could restore bone function and structure in an ovariectomized (OVX)-induced osteoporotic mouse model. Thus Zfp467 play an important role in ADSCs differentiation to adipocyte and osteoblast. This has relevance to therapeutic interventions in osteoporosis, including si-Zfp467-based therapies currently available, and may be of relevance for the use of adipose-derived stem cells for tissue engineering

rs4919510 in hsa-mir-608 Is Associated with Outcome but Not Risk of Colorectal Cancer

Colorectal cancer is the third most incident cancer and cause of cancer-related death in the United States. MicroRNAs, a class of small non-coding RNAs, have been implicated in the pathogenesis and prognosis of colorectal cancer, although few studies have examined the relationship between germline mutation in the microRNAs with risk and prognosis. We therefore investigated the association between a SNP in hsa-mir-608, which lies within the 10q24 locus, and colorectal cancer.A cohort consisting of 245 cases and 446 controls was genotyped for rs4919510. The frequency of the GG genotype was significantly higher in African Americans (15%) compared to Caucasians (3%) controls. There was no significant association between rs4919510 and colorectal cancer risk (African American: OR(GG vs. CC) 0.89 [95% CI, 0.41-1.80]) (Caucasian: OR(GG vs. CC) 1.76, ([95% CI, 0.48-6.39]). However, we did observe an association with survival. The GG genotype was associated with an increased risk of death in Caucasians (HR(GG vs. CC) 3.54 ([95% CI, 1.38-9.12]) and with a reduced risk of death in African Americans (HR(GG vs. CC) 0.36 ([95% CI 0.12-1.07).These results suggest that rs4910510 may be associated with colorectal cancer survival in a manner that is dependent on race

Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset

<p>Abstract</p> <p>Background</p> <p>Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interactions may be modelled by a Bayesian Network (BN) that represents the presence of direct interactions from regulators to regulees by conditional probability distributions. We used enhanced evolutionary algorithms to stochastically evolve a set of candidate BN structures and found the model that best fits data without prior knowledge.</p> <p>Results</p> <p>We proposed various evolutionary strategies suitable for the task and tested our choices using simulated data drawn from a given bio-realistic network of 35 nodes, the so-called insulin network, which has been used in the literature for benchmarking. We assessed the inferred models against this reference to obtain statistical performance results. We then compared performances of evolutionary algorithms using two kinds of recombination operators that operate at different scales in the graphs. We introduced a niching strategy that reinforces diversity through the population and avoided trapping of the algorithm in one local minimum in the early steps of learning. We show the limited effect of the mutation operator when niching is applied. Finally, we compared our best evolutionary approach with various well known learning algorithms (MCMC, K2, greedy search, TPDA, MMHC) devoted to BN structure learning.</p> <p>Conclusion</p> <p>We studied the behaviour of an evolutionary approach enhanced by niching for the learning of gene regulatory networks with BN. We show that this approach outperforms classical structure learning methods in elucidating the original model. These results were obtained for the learning of a bio-realistic network and, more importantly, on various small datasets. This is a suitable approach for learning transcriptional regulatory networks from real datasets without prior knowledge.</p

Using Evolutionary Conserved Modules in Gene Networks as a Strategy to Leverage High Throughput Gene Expression Queries

Background: Large-scale gene expression studies have not yielded the expected insight into genetic networks that control complex processes. These anticipated discoveries have been limited not by technology, but by a lack of effective strategies to investigate the data in a manageable and meaningful way. Previous work suggests that using a pre-determined seednetwork of gene relationships to query large-scale expression datasets is an effective way to generate candidate genes for further study and network expansion or enrichment. Based on the evolutionary conservation of gene relationships, we test the hypothesis that a seed network derived from studies of retinal cell determination in the fly, Drosophila melanogaster, will be an effective way to identify novel candidate genes for their role in mouse retinal development. Methodology/Principal Findings: Our results demonstrate that a number of gene relationships regulating retinal cell differentiation in the fly are identifiable as pairwise correlations between genes from developing mouse retina. In addition, we demonstrate that our extracted seed-network of correlated mouse genes is an effective tool for querying datasets and provides a context to generate hypotheses. Our query identified 46 genes correlated with our extracted seed-network members. Approximately 54% of these candidates had been previously linked to the developing brain and 33% had been previously linked to the developing retina. Five of six candidate genes investigated further were validated by experiments examining spatial and temporal protein expression in the developing retina. Conclusions/Significance: We present an effective strategy for pursuing a systems biology approach that utilizes an evolutionary comparative framework between two model organisms, fly and mouse. Future implementation of this strategy will be useful to determine the extent of network conservation, not just gene conservation, between species and will facilitate the use of prior biological knowledge to develop rational systems-based hypotheses

Inhibition of IL-10 Production by Maternal Antibodies against Group B Streptococcus GAPDH Confers Immunity to Offspring by Favoring Neutrophil Recruitment

Group B Streptococcus (GBS) is the leading cause of neonatal pneumonia, septicemia, and meningitis. We have previously shown that in adult mice GBS glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is an extracellular virulence factor that induces production of the immunosuppressive cytokine interleukin-10 (IL-10) by the host early upon bacterial infection. Here, we investigate whether immunity to neonatal GBS infection could be achieved through maternal vaccination against bacterial GAPDH. Female BALB/c mice were immunized with rGAPDH and the progeny was infected with a lethal inoculum of GBS strains. Neonatal mice born from mothers immunized with rGAPDH were protected against infection with GBS strains, including the ST-17 highly virulent clone. A similar protective effect was observed in newborns passively immunized with anti-rGAPDH IgG antibodies, or F(ab')2 fragments, indicating that protection achieved with rGAPDH vaccination is independent of opsonophagocytic killing of bacteria. Protection against lethal GBS infection through rGAPDH maternal vaccination was due to neutralization of IL-10 production soon after infection. Consequently, IL-10 deficient (IL-10−/−) mice pups were as resistant to GBS infection as pups born from vaccinated mothers. We observed that protection was correlated with increased neutrophil trafficking to infected organs. Thus, anti-rGAPDH or anti-IL-10R treatment of mice pups before GBS infection resulted in increased neutrophil numbers and lower bacterial load in infected organs, as compared to newborn mice treated with the respective control antibodies. We showed that mothers immunized with rGAPDH produce neutralizing antibodies that are sufficient to decrease IL-10 production and induce neutrophil recruitment into infected tissues in newborn mice. These results uncover a novel mechanism for GBS virulence in a neonatal host that could be neutralized by vaccination or immunotherapy. As GBS GAPDH is a structurally conserved enzyme that is metabolically essential for bacterial growth in media containing glucose as the sole carbon source (i.e., the blood), this protein constitutes a powerful candidate for the development of a human vaccine against this pathogen

Lung macrophage scavenger receptor SR-A6 (MARCO) is an adenovirus type-specific virus entry receptor

<div><p>Macrophages are a diverse group of phagocytic cells acting in host protection against stress, injury, and pathogens. Here, we show that the scavenger receptor SR-A6 is an entry receptor for human adenoviruses in murine alveolar macrophage-like MPI cells, and important for production of type I interferon. Scavenger receptors contribute to the clearance of endogenous proteins, lipoproteins and pathogens. Knockout of SR-A6 in MPI cells, anti-SR-A6 antibody or the soluble extracellular SR-A6 domain reduced adenovirus type-C5 (HAdV-C5) binding and transduction. Expression of murine SR-A6, and to a lower extent human SR-A6 boosted virion binding to human cells and transduction. Virion clustering by soluble SR-A6 and proximity localization with SR-A6 on MPI cells suggested direct adenovirus interaction with SR-A6. Deletion of the negatively charged hypervariable region 1 (HVR1) of hexon reduced HAdV-C5 binding and transduction, implying that the viral ligand for SR-A6 is hexon. SR-A6 facilitated macrophage entry of HAdV-B35 and HAdV-D26, two important vectors for transduction of hematopoietic cells and human vaccination. The study highlights the importance of scavenger receptors in innate immunity against human viruses.</p></div