Repressive Gene Regulation Synchronizes Development with Cellular Metabolism.

Metabolic conditions affect the developmental tempo of animals. Developmental gene regulatory networks (GRNs) must therefore synchronize their dynamics with a variable timescale. We find that layered repression of genes couples GRN output with variable metabolism. When repressors of transcription or mRNA and protein stability are lost, fewer errors in Drosophila development occur when metabolism is lowered. We demonstrate the universality of this phenomenon by eliminating the entire microRNA family of repressors and find that development to maturity can be largely rescued when metabolism is reduced. Using a mathematical model that replicates GRN dynamics, we find that lowering metabolism suppresses the emergence of developmental errors by curtailing the influence of auxiliary repressors on GRN output. We experimentally show that gene expression dynamics are less affected by loss of repressors when metabolism is reduced. Thus, layered repression provides robustness through error suppression and may provide an evolutionary route to a shorter reproductive cycle.

miR-9a minimizes the phenotypic impact of genomic diversity by buffering a transcription factor.

Gene expression has to withstand stochastic, environmental, and genomic perturbations. For example, in the latter case, 0.5%-1% of the human genome is typically variable between any two unrelated individuals. Such diversity might create problematic variability in the activity of gene regulatory networks and, ultimately, in cell behaviors. Using multigenerational selection experiments, we find that for the Drosophila proneural network, the effect of genomic diversity is dampened by miR-9a-mediated regulation of senseless expression. Reducing miR-9a regulation of the Senseless transcription factor frees the genomic landscape to exert greater phenotypic influence. Whole-genome sequencing identified genomic loci that potentially exert such effects. A larger set of sequence variants, including variants within proneural network genes, exhibits these characteristics when miR-9a concentration is reduced. These findings reveal that microRNA-target interactions may be a key mechanism by which the impact of genomic diversity on cell behavior is dampened.

MicroRNA function in Drosophila melanogaster.

Over the last decade, microRNAs have emerged as critical regulators in the expression and function of animal genomes. This review article discusses the relationship between microRNA-mediated regulation and the biology of the fruit fly Drosophila melanogaster. We focus on the roles that microRNAs play in tissue growth, germ cell development, hormone action, and the development and activity of the central nervous system. We also discuss the ways in which microRNAs affect robustness. Many gene regulatory networks are robust; they are relatively insensitive to the precise values of reaction constants and concentrations of molecules acting within the networks. MicroRNAs involved in robustness appear to be nonessential under uniform conditions used in conventional laboratory experiments. However, the robust functions of microRNAs can be revealed when environmental or genetic variation otherwise has an impact on developmental outcomes.

Single-cell Senseless protein analysis reveals metastable states during the transition to a sensory organ fate.

Cell fate decisions can be envisioned as bifurcating dynamical systems, and the decision that Drosophila cells make during sensory organ differentiation has been described as such. We extended these studies by focusing on the Senseless protein which orchestrates sensory cell fate transitions. Wing cells contain intermediate Senseless numbers before their fate transition, after which they express much greater numbers of Senseless molecules as they differentiate. However, the dynamics are inconsistent with it being a simple bistable system. Cells with intermediate Senseless are best modeled as residing in four discrete states, each with a distinct protein number and occupying a specific region of the tissue. Although the states are stable over time, the number of molecules in each state vary with time. The fold change in molecule number between adjacent states is invariant and robust to absolute protein number variation. Thus, cells transitioning to sensory fates exhibit metastability with relativistic properties.

Ordered patterning of the sensory system is susceptible to stochastic features of gene expression.

Sensory neuron numbers and positions are precisely organized to accurately map environmental signals in the brain. This precision emerges from biochemical processes within and between cells that are inherently stochastic. We investigated impact of stochastic gene expression on pattern formation, focusing on senseless (sens), a key determinant of sensory fate in Drosophila. Perturbing microRNA regulation or genomic location of sens produced distinct noise signatures. Noise was greatly enhanced when both sens alleles were present in homologous loci such that each allele was regulated in trans by the other allele. This led to disordered patterning. In contrast, loss of microRNA repression of sens increased protein abundance but not sensory pattern disorder. This suggests that gene expression stochasticity is a critical feature that must be constrained during development to allow rapid yet accurate cell fate resolution.

Spindle-E cycling between nuage and cytoplasm is controlled by Qin and PIWI proteins.

Transposable elements (TEs) are silenced in germ cells by a mechanism in which PIWI proteins generate and use PIWI-interacting ribonucleic acid (piRNA) to repress expression of TE genes. piRNA biogenesis occurs by an amplification cycle in microscopic organelles called nuage granules, which are localized to the outer face of the nuclear envelope. One cofactor required for amplification is the helicase Spindle-E (Spn-E). We found that the Spn-E protein physically associates with the Tudor domain protein Qin and the PIWI proteins Aubergine (Aub) and Argonaute3 (Ago3). Spn-E and Qin proteins are mutually dependent for their exit from nuage granules, whereas Spn-E and both Aub and Ago3 are mutually dependent for their entry or retention in nuage. The result is a dynamic cycling of Spn-E and its associated factors in and out of nuage granules. This implies that nuage granules can be considered to be hubs for active, mobile, and transient complexes. We suggest that this is in some way coupled with the execution of the piRNA amplification cycle.

SUMO-Enriched Proteome for Drosophila Innate Immune Response.

Small ubiquitin-like modifier (SUMO) modification modulates the expression of defense genes in Drosophila, activated by the Toll/nuclear factor-κB and immune-deficient/nuclear factor-κB signaling networks. We have, however, limited understanding of the SUMO-modulated regulation of the immune response and lack information on SUMO targets in the immune system. In this study, we measured the changes to the SUMO proteome in S2 cells in response to a lipopolysaccharide challenge and identified 1619 unique proteins in SUMO-enriched lysates. A confident set of 710 proteins represents the immune-induced SUMO proteome and analysis suggests that specific protein domains, cellular pathways, and protein complexes respond to immune stress. A small subset of the confident set was validated by in-bacto SUMOylation and shown to be bona-fide SUMO targets. These include components of immune signaling pathways such as Caspar, Jra, Kay, cdc42, p38b, 14-3-3ε, as well as cellular proteins with diverse functions, many being components of protein complexes, such as prosß4, Rps10b, SmD3, Tango7, and Aats-arg. Caspar, a human FAF1 ortholog that negatively regulates immune-deficient signaling, is SUMOylated at K551 and responds to treatment with lipopolysaccharide in cultured cells. Our study is one of the first to describe SUMO proteome for the Drosophila immune response. Our data and analysis provide a global framework for the understanding of SUMO modification in the host response to pathogens.