RESUMEN
In multicellular and even single-celled organisms, individual components are interconnected at multiscale levels to produce enormously complex biological networks that help these systems maintain homeostasis for development and environmental adaptation. Systems biology studies initially adopted network analysis to explore how relationships between individual components give rise to complex biological processes. Network analysis has been applied to dissect the complex connectivity of mammalian brains across different scales in time and space in The Human Brain Project. In plant science, network analysis has similarly been applied to study the connectivity of plant components at the molecular, subcellular, cellular, organic, and organism levels. Analysis of these multiscale networks contributes to our understanding of how genotype determines phenotype. In this review, we summarized the theoretical framework of plant multiscale networks and introduced studies investigating plant networks by various experimental and computational modalities. We next discussed the currently available analytic methodologies and multi-level imaging techniques used to map multiscale networks in plants. Finally, we highlighted some of the technical challenges and key questions remaining to be addressed in this emerging field.
Asunto(s)
Diagnóstico por Imagen , Modelos Biológicos , Células Vegetales/fisiología , Fenómenos Fisiológicos de las Plantas , Biología de Sistemas , Genotipo , FenotipoRESUMEN
The mechanism of latent tuberculosis (TB) infection remains elusive. Several host factors that are involved in this complex process were previously identified. Micro RNAs (miRNAs) are endogenous â¼22 nt RNAs that play important regulatory roles in a wide range of biological processes. Several studies demonstrated the clinical usefulness of miRNAs as diagnostic or prognostic biomarkers in various malignancies and in a few nonmalignant diseases. To study the role of miRNAs in the transition from latent to active TB and to discover candidate biomarkers of this transition, we used human miRNA microarrays to probe the transcriptome of peripheral blood mononuclear cells (PBMCs) in patients with active TB, latent TB infection (LTBI), and healthy controls. Using the software package BRB Array Tools for data analyses, 17 miRNAs were differentially expressed between the three groups (P<0.01). Hierarchical clustering of the 17 miRNAs expression profiles showed that individuals with active TB clustered independently of individuals with LTBI or from healthy controls. Using the predicted target genes and previously published genome-wide transcriptional profiles, we constructed the regulatory networks of miRNAs that were differentially expressed between active TB and LTBI. The regulatory network revealed that several miRNAs, with previously established functions in hematopoietic cell differentiation and their target genes may be involved in the transition from latent to active TB. These results increase the understanding of the molecular basis of LTBI and confirm that some miRNAs may control gene expression of pathways that are important for the pathogenesis of this infectious disease.