Expression patterns of FSHD-causing DUX4 and myogenic transcription factors PAX3 and PAX7 are spatially distinct in differentiating human stem cell cultures.

BACKGROUND: Facioscapulohumeral muscular dystrophy (FSHD) is most commonly inherited in an autosomal dominant pattern and caused by the abnormal expression of DUX4 in skeletal muscle. The DUX4 transcription factor has DNA binding domains similar to several paired class homeotic transcription factors, but only myogenic factors PAX3 and PAX7 rescue cell viability when co-expressed with DUX4 in mouse myoblasts. This observation suggests competition for DNA binding sites in satellite cells might limit muscle repair and may be one aspect of DUX4-associated myotoxicity. The competition hypothesis requires that DUX4 and PAX3/7 be expressed in the same cells at some point during development or in adult tissues. We modeled myogenesis using human isogenic iPS and ES cells and examined expression patterns of DUX4, PAX3, and PAX7 to determine if conditions that promote PAX3 and PAX7 expression in cell culture also promote DUX4 expression in the same cells. METHODS: Isogenic iPSCs were generated from human fibroblasts of two FSHD-affected individuals with somatic mosaicism. Clones containing the shortened FSHD-causing D4Z4 array or the long non-pathogenic array were isolated from the same individuals. We also examined myogenesis in commercially available hES cell lines derived from FSHD-affected and non-affected embryos. DUX4, PAX3, and PAX7 messenger RNAs (mRNAs) were quantified during a 40-day differentiation protocol, and antibodies were used to identify cell types in different stages of differentiation to determine if DUX4 and PAX3 or PAX7 are present in the same cells. RESULTS: Human iPS and ES cells differentiated into skeletal myocytes as evidenced by Titin positive multinucleated fibers appearing toward the end of a 40-day differentiation protocol. PAX3 and PAX7 were expressed at similar times during differentiation, and DUX4 positive nuclei were seen at terminal stages of differentiation in cells containing the short D4Z4 arrays. Nuclei that expressed both DUX4 and PAX3, or DUX4 and PAX7 were not observed after examining immunostained nuclei at five different time points during myogenic differentiation of pluripotent cells. CONCLUSIONS: We conclude that DUX4, PAX3, and PAX7 have distinct expression patterns during myogenic differentiation of stem cells. Our findings are consistent with the hypothesis that muscle damage in FSHD is due to DUX4-mediated toxicity causing destruction of terminally differentiated myofibers. While these studies examine DUX4, PAX3, and PAX7 expression patterns during stem cell myogenesis, they should not be generalized to tissue repair in adult muscle tissue.

Integrated Modeling of Gene Regulatory and Metabolic Networks in Mycobacterium tuberculosis.

Mycobacterium tuberculosis (MTB) is the causative bacterium of tuberculosis, a disease responsible for over a million deaths worldwide annually with a growing number of strains resistant to antibiotics. The development of better therapeutics would greatly benefit from improved understanding of the mechanisms associated with MTB responses to different genetic and environmental perturbations. Therefore, we expanded a genome-scale regulatory-metabolic model for MTB using the Probabilistic Regulation of Metabolism (PROM) framework. Our model, MTBPROM2.0, represents a substantial knowledge base update and extension of simulation capability. We incorporated a recent ChIP-seq based binding network of 2555 interactions linking to 104 transcription factors (TFs) (representing a 3.5-fold expansion of TF coverage). We integrated this expanded regulatory network with a refined genome-scale metabolic model that can correctly predict growth viability over 69 source metabolite conditions and predict metabolic gene essentiality more accurately than the original model. We used MTBPROM2.0 to simulate the metabolic consequences of knocking out and overexpressing each of the 104 TFs in the model. MTBPROM2.0 improves performance of knockout growth defect predictions compared to the original PROM MTB model, and it can successfully predict growth defects associated with TF overexpression. Moreover, condition-specific models of MTBPROM2.0 successfully predicted synergistic growth consequences of overexpressing the TF whiB4 in the presence of two standard anti-TB drugs. MTBPROM2.0 can screen in silico condition-specific transcription factor perturbations to generate putative targets of interest that can help prioritize future experiments for therapeutic development efforts.