Electronically subtracting expression patterns from a mixed cell population

MOTIVATION: Biological samples frequently contain multiple cell-types that each can play a crucial role in the development and/or regulation of adjacent cells or tissues. The search for biomarkers, or expression patterns of, one cell-type in those samples can be a complex and time-consuming process. Ordinarily, extensive laboratory bench work must be performed to separate the mixed cell population into its subcomponents, such that each can be accurately characterized. RESULTS: We have developed a methodology to electronically subtract gene expression in one or more components of a mixed cell population from a mixture, to reveal the expression patterns of other minor or difficult to isolate components. Examination of simulated data indicates that this procedure can reliably determine the expression patterns in cell-types that contribute as little as 5% of the total expression in a mixed cell population. We re-analyzed microarray expression data from the viral infection of macrophages and from the T-cells of wild type and Foxp3 deletion mice. Using our subtraction methodology, we were able to substantially improve the identification of genes involved in processes of subcomponent portions of these samples.     

A comprehensive mouse IBD database for the efficient localization of quantitative trait loci

Traditional fine-mapping approaches in mouse genetics that go from a linkage region to a candidate gene are very costly and time consuming. Shared ancestry regions, along with the combination of genetics and genomics approaches, provide a powerful tool to shorten the time and effort required to identify a causative gene. In this article we present a novel methodology that predicts IBD (identical by descent) regions between pairs of inbred strains using single nucleotide polymorphism (SNP) maps. We have validated this approach by comparing the IBD regions, estimated using different algorithms, to the results derived using the sequence information in the strains present in the Celera Mouse Database. We showed that based on the current publicly available SNP genotypes, large IBD regions (>1 Mb) can be identified successfully. By assembling a list of 21,514 SNPs in 61 common inbred strains, we inferred IBD regions between all pairs of strains and confirmed, for the first time, that existing quantitative trait genes (QTG) and susceptibility genes all lie outside of IBD regions. We also illustrated how knowledge of IBD structures can be applied to strain selection for future crosses. We have made our results available for data mining and download through a public website ( ). Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users.     

Efficient gene transfer in Synechococcus sp. strains PCC 7942 and PCC 6301 by interspecies conjugation and chromosomal recombination.

We developed a versatile, efficient genetic transfer method for Synechococcus sp. strains PCC 7942 and PCC 6301 that exceeds natural transformation efficiencies by orders of magnitude. As a test case, we complemented a histidine auxotroph and identified a hisS homolog of PCC 7942 as the complementing gene.     

Heterogeneity in SDF-1 expression defines the vasculogenic potential of adult cardiac progenitor cells

Rationale

The adult myocardium has been reported to harbor several classes of multipotent progenitor cells (CPCs) with tri-lineage differentiation potential. It is not clear whether c-kit+CPCs represent a uniform precursor population or a more complex mixture of cell types.

Objective

To characterize and understand vasculogenic heterogeneity within c-kit+presumptive cardiac progenitor cell populations.

Methods and Results

c-kit+, sca-1+ CPCs obtained from adult mouse left ventricle expressed stem cell-associated genes, including Oct-4 and Myc, and were self-renewing, pluripotent and clonogenic. Detailed single cell clonal analysis of 17 clones revealed that most (14/17) exhibited trilineage differentiation potential. However, striking morphological differences were observed among clones that were heritable and stable in long-term culture. 3 major groups were identified: round (7/17), flat or spindle-shaped (5/17) and stellate (5/17). Stellate morphology was predictive of vasculogenic differentiation in Matrigel. Genome-wide expression studies and bioinformatic analysis revealed clonally stable, heritable differences in stromal cell-derived factor-1 (SDF-1) expression that correlated strongly with stellate morphology and vasculogenic capacity. Endogenous SDF-1 production contributed directly to vasculogenic differentiation: both shRNA-mediated knockdown of SDF-1 and AMD3100, an antagonist of the SDF-1 receptor CXC chemokine Receptor-4 (CXCR4), reduced tube-forming capacity, while exogenous SDF-1 induced tube formation by 2 non-vasculogenic clones. CPCs producing SDF-1 were able to vascularize Matrigel dermal implants in vivo, while CPCs with low SDF-1 production were not.

Conclusions

Clonogenic c-kit+, sca-1+ CPCs are heterogeneous in morphology, gene expression patterns and differentiation potential. Clone-specific levels of SDF-1 expression both predict and promote development of a vasculogenic phenotype via a previously unreported autocrine mechanism.     

Identifying consensus disease pathways in Parkinson's disease using an integrative systems biology approach

Parkinson's disease (PD) has had six genome-wide association studies (GWAS) conducted as well as several gene expression studies. However, only variants in MAPT and SNCA have been consistently replicated. To improve the utility of these approaches, we applied pathway analyses integrating both GWAS and gene expression. The top 5000 SNPs (p<0.01) from a joint analysis of three existing PD GWAS were identified and each assigned to a gene. For gene expression, rather than the traditional comparison of one anatomical region between sets of patients and controls, we identified differentially expressed genes between adjacent Braak regions in each individual and adjusted using average control expression profiles. Over-represented pathways were calculated using a hyper-geometric statistical comparison. An integrated, systems meta-analysis of the over-represented pathways combined the expression and GWAS results using a Fisher's combined probability test. Four of the top seven pathways from each approach were identical. The top three pathways in the meta-analysis, with their corrected p-values, were axonal guidance (p = 2.8E-07), focal adhesion (p = 7.7E-06) and calcium signaling (p = 2.9E-05). These results support that a systems biology (pathway) approach will provide additional insight into the genetic etiology of PD and that these pathways have both biological and statistical support to be important in PD.     

Developing combinatorial multi-component therapies (CMCT) of drugs that are more specific and have fewer side effects than traditional one drug therapies

Drugs designed for a specific target are always found to have multiple effects. Rather than hope that one bullet can be designed to hit only one target, nonlinear interactions across genomic and proteomic networks could be used to design Combinatorial Multi-Component Therapies (CMCT) that are more targeted with fewer side effects. We show here how computational approaches can be used to predict which combinations of drugs would produce the best effects. Using a nonlinear model of how the output effect depends on multiple input drugs, we show that an artificial neural network can accurately predict the effect of all 2¹⁵ = 32,768 combinations of drug inputs using only the limited data of the output effect of the drugs presented one-at-a-time and pairs-at-a-time.