Relatively recently (2019) I read two very interesting papers, each with quite extraordinary claims regarding the regulation of genetic expression under specific cellular growth states.

The first paper claims that most SUMO conjugation events are not required for normal growth, and might therefore serve a protective, preemptive role in anticipation of stress-inducing changes in the environment. However, reduced sumoylation did not impact growth when cells were challenged with osmotic, oxidative, and ethanol stress, all of which can trigger elevated sumoylation in the SUMO stress response (SSR). … Reduced cellular sumoylation levels did elicit sensitivity to elevated temperatures, however, particularly in the Ubc9-AA and ubc9-1strains for which higher temperatures are lethal, consistent with the finding that sumoylation facilitates heat tolerance in human cells and plants.

In the second paper, researchers found that fruit flies – with slowed metabolic rates – could live without any microRNAs, which was previously thought impossible! When repressors of transcription or mRNA and protein stability are lost, fewer errors in Drosophila development occur when metabolism is lowered. These authors demonstrated the universality of this phenomenon by eliminating the entire microRNA family of repressors, finding that development to maturity could be largely rescued when metabolism was reduced. It appeared that lowering metabolism suppressed the emergence of developmental errors …

 


Normal Levels of Cellular Sumoylation Are Largely Dispensable for Growth but Facilitate Heat Tolerance in Yeast

Marjan Moallem et al. (v1: 2019-09-07; v2: 2019-11-27). Department of Biology, York University, Toronto, Ontario. DOI: 10.1101/761759

Keywords, phrases: ubiquitination; sumoylation; sumo conjugation and deconjugation; conjugase ubc9; sumo-targeted ubiquitin ligases; unfolded proteins

ABSTRACT

Sumoylation is an essential, conserved protein modification with hundreds of targets. Compared to the related modification ubiquitination, a small number of enzymes are involved in SUMO conjugation and deconjugation, including a single conjugase, Ubc9, in yeast and mammals. This suggests that cells can simultaneously control the sumoylation level of numerous proteins by regulating just one enzyme of the SUMO pathway. Such modulated levels of cellular sumoylation are observed in response to a number of stress conditions, which typically cause a rapid and dramatic increase in overall sumoylation. Here, we demonstrate that ploidy, culture density, and nutrient availability also affect global sumoylation levels in yeast. To determine the effects of modulated cellular sumoylation levels on cell growth, we examined engineered yeast strains that harbour reduced global sumoylation. Remarkably, reducing SUMO conjugation levels by >75% has no effect on cell fitness, indicating that most sumoylation events are not required for normal growth. Surprisingly, strains with constitutively low sumoylation levels show no growth defects when exposed to a number of stress conditions except that they are highly sensitive to elevated temperatures. Consistent with the fact that Ubc9 and SUMO are essential, however, cells displaying less than ∼5% of normal sumoylation levels show significantly impaired growth, even at normal temperatures. Finally, we demonstrate that many sumoylation events are highly transient, requiring constant de novo sumoylation to maintain steady state levels. Together, our results suggest that cells need only a low level of sumoylation for growth, but that normal levels are required pre-emptively to facilitate survival when temperatures rise.

INTRODUCTION

Nearly one tenth of all human and budding yeast proteins have been identified as putative targets of SUMO post-translational modification in normal growth conditions, many of which are involved in gene expression and chromatin maintenance or regulation (Makhnevych et al. 2009; Albuquerque et al. 2015; Hendriks et al. 2017; Esteras et al. 2017; Zhao 2018). Sumoylation involves the covalent attachment of a SUMO peptide to the side chain of specific Lys residues, through isopeptide bonds, that often lie within a SUMO consensus motif (Flotho and Melchior 2013; Hendriks et al. 2017). The effects of protein sumoylation are largely target-specific, but include altered localization, activity, stability, and association with chromatin (Flotho and Melchior 2013; Chymkowitch et al. 2015; Rosonina et al. 2017; Zhao 2018). At the molecular level, these effects are usually mediated by altered protein-protein interactions, with SUMO occluding the interaction of the sumoylated target with binding partners in some cases, or facilitating interactions with binding partners that harbour SUMO interacting motifs (SIMs) in other cases (Gareau and Lima 2010; Flotho and Melchior 2013). Although many proteins are sumoylated, typically, only a small fraction (<5%) of polypeptides of each target protein is modified at any one time, which is partly the result of the constitutive activity of SUMO proteases, including the SENP family of isopeptidases in human cells (Hickey et al. 2012). There are two SUMO proteases in yeast, Ulp1, which is essential for viability, and Ulp2, which prevents accumulation of polysumoylate chains that form when conjugated SUMO peptides themselves become sumoylated (Li and Hochstrasser 2000; Bylebyl et al. 2003).

The name SUMO, an acronym for small ubiquitin-like modifier, derives from its similarity to the eukaryotic protein modifier, ubiquitin (Mahajan et al. 1997). In addition to structural similarity between SUMO and ubiquitin peptides, SUMO conjugation involves a 4cascade of enzymatic activities that is analogous to ubiquitination: activation by an E1 class enzyme and target conjugation by E2 enzymes, which can be facilitated by E3 SUMO ligases that enhance sumoylation and target Lys specificity (Bayer et al. 1998; Sheng and Liao 2002; Flotho and Melchior 2013). In sharp contrast with ubiquitination, however, the number of SUMO conjugation and deconjugation enzymes is small, with both yeast and mammals harboring a single conjugase, Ubc9. As such, eukaryotic cells can simultaneously control the sumoylation level of hundreds of substrate proteins by regulating the activity of just one SUMO conjugating or deconjugating enzyme at a time. For example, exposure of budding yeast to ethanol triggers the nucleolar sequestration of the SUMO protease Ulp1, which results in a global increase in protein sumoylation within minutes (Sydorskyy et al. 2010).

Such rapid increases in global levels of SUMO conjugation occur in response to a variety of stress conditions, and are collectively referred to as the SUMO stress response (SSR; (Lewicki et al. 2015; Enserink 2015; Niskanen and Palvimo 2017; Nguéa P et al. 2019)). Exposure of mammalian cells to heat, oxidative, osmotic, or ethanol stress results in a spike in sumoylation levels caused by increased conjugation of numerous proteins with SUMO isoforms SUMO2 and/or SUMO3, specifically (Saitoh and Hinchey 2000; Golebiowski et al. 2009; Hendriks et al. 2014). As with sequestration of Ulp1 in yeast upon exposure to ethanol, the SSR that occurs with heat shock in human cells is at least partly caused by inactivation of multiple SENPs, suggesting that constitutive desumoylation is required for maintaining steady state levels of sumoylation (Pinto et al. 2012). In addition to ethanol exposure, yeast also respond with dramatically elevated SUMO conjugation levels in response to oxidative or osmotic conditions (Zhou et al. 2004; Lewicki et al. 2015). Inhibitors of transcription virtually eliminate the SSR in yeast, implying that elevated sumoylation is largely a consequence of stress-induced transcriptional reprogramming and is not necessarily linked to the stress itself (Lewicki et al. 2015). However, SUMO2/3 isoforms are required for human cells to survive heat shock, and elevated levels of sumoylation appear to have a protective effect on neuronal tissue during exposure to reduced oxygen and glucose (Lee et al. 2009, 2011; Golebiowski et al. 2009; Flotho and Melchior 2013; Guo and Henley 2014). This suggests that elevated sumoylation itself serves a role in the adaptation of cells to unfavourable conditions, but the physiological effects of modulated cellular sumoylation levels are largely unknown.

To explore this, here we examined how altered sumoylation levels affect cell fitness in yeast. Besides stress, we found that cellular SUMO conjugation levels change with ploidy, culture density, and nutrient availability. By examining mutant yeast strains that harbour reduced sumoylation levels, either constitutively or conditionally, we determined that dramatic reduction in global sumoylation is well-tolerated in yeast grown in normal, non-stress conditions. However, reduced sumoylation results in increased sensitivity to high temperature, but, surprisingly, it had no effect on growth in response to other types of stress, including oxidative, osmotic and ethanol stress. Finally, we demonstrate that blocking de novo sumoylation results in a rapid and dramatic reduction of SUMO conjugation levels, suggesting that the modification is highly transient for many conjugates. Our results support a model in which sumoylation plays a largely pre-emptive role, specifically in preparing cells for potential exposure to high temperatures.

RESULTS

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DISCUSSION

Over 550 proteins have been identified as SUMO conjugates in normally growing yeast through proteomics analyses ((Makhnevych et al. 2009; Albuquerque et al. 2015; Esteras et al. 2017), and addition studies cited therein). Whereas, in some published studies, immunoblots show few yeast SUMO conjugates except in stress conditions, our SUMO immunoblots readily detect numerous sumoylated species in non-stressed yeast, indicating that they are a good reflection of the sumoylation status of the cells. As such, we were able to identify factors and conditions, in addition to stress, that affect global sumoylation in yeast. Specifically, we found that diploid cells harbour less sumoylation than their haploid counterparts, and that nutrient availability has a positive effect on levels of SUMO conjugation. This was apparent by comparing sumoylation levels in yeast grown in rich versus synthetic medium, and by monitoring sumoylation in a growing liquid culture. Sumoylation levels were greatest during exponential growth, but dropped dramatically with the diauxic shift, which occurs as glucose becomes depleted. Typically, to elicit a stress response, yeast cultures are treated with stressors when they are growing exponentially, as in Fig. 1B. This indicates that stress can elevate sumoylation levels beyond the maximal level seen in cultures during normal growth. These results demonstrate that sumoylation levels can be shifted dramatically both upward, as during stress, and downward, when cultures reach saturation.

Considering that many SUMO targets are involved in gene expression, metabolism, and cell cycle, it might be expected that dramatic shifts in overall SUMO conjugation affect cell growth (Makhnevych et al. 2009; Albuquerque et al. 2015; Hendriks et al. 2017; Esteras et al. 2017). Our initial strategies to explore this involved upregulating the abundance of the SUMO conjugase, Ubc9, or the SUMO peptide itself, as similar approaches have been used previously to elevate sumoylation levels in mammalian systems (Lee et al. 2009, 2011). However, in our analysis, global sumoylation levels were unaffected, indicating that Ubc9 and SUMO peptides are not limiting, and that it is unlikely that yeast cells modulate sumoylation levels by regulating the abundance of these proteins. This is consistent with the finding of others that cells can elevate sumoylation globally by inactivating or deactivating SUMO proteases (Sydorskyy et al. 2010; Pinto et al. 2012; Lewicki et al. 2015).

To examine the effects of reduced global sumoylation on cell fitness, we first used the Anchor Away methodology with Ubc9 to conditionally block de novo sumoylation events in the nucleus (Haruki et al. 2008). Nuclear depletion of Ubc9 by this system had a surprisingly rapid effect, in which most SUMO conjugations disappeared within a few minutes. Although this might reflect that SUMO modifications are highly labile, there is no evidence that the dramatic reduction in SUMO conjugation levels was due to desumoylation, as there was no concomitant increase in the abundance of free SUMO. This suggests that the bulk of sumoylated proteins detected in the Ubc9-AA strain are rapidly degraded. Consistent with this, many sumoylated proteins, particularly those that are polysumoylated, can be targeted for degradation through the action of SUMO-targeted ubiquitin ligases (STUbLs), that bind and ubiquitinate SUMO chains, which directs the conjugated proteins to the 26S proteasome for proteolysis (Sriramachandran and Dohmen 2014). However, inhibition of the 26S proteasome using MG132 had no effect on the disappearance of SUMO conjugates when Ubc9 was depleted, suggesting that many sumoylated proteins in yeast are destined for rapid degradation through a pathway that does not involve typical ubiquitin-mediated proteolysis. Alternatively, the disappearance of the SUMO signal might be attributed to frequent desumoylation of targets by the essential SUMO protease Ulp1, followed by the rapid degradation of the SUMO peptide itself. However, we were unable to generate viable yeast strains harbouring defective Ulp1 mutants in the Ubc9-AA background to test this.

Treatment of mammalian cells with proteasome inhibitors, such as MG132, leads to a significant increase in SUMO conjugates, primarily with the SUMO2/3 isoforms, which includes accumulation of proteins that are modified with both SUMO and ubiquitin (Schimmel et al. 2008; Tatham et al. 2011; Lamoliatte et al. 2017). As this MG132-dependent increase in sumoylation levels was shown to be dependent on protein synthesis, it is believed that misfolded newly synthesized polypeptides are normally targeted by sumoylation as part of their degradation pathway, and that these become detectable upon proteasomal inhibition with MG132 treatment (Tatham et al. 2011; Častorálová et al. 2012). In our analysis, proteasomal inhibition with MG132 did cause an accumulation of polyubiquitinated proteins, as expected, but no significant change to overall sumoylation levels was observed. Although these experiments were performed in the Ubc9-AA strain, which harbours ~25% of the normal levels of SUMO conjugation, this observation suggests that any accumulation of misfolded proteins destined for proteasomal degradation that might occur in budding yeast does not trigger a sumoylation response as it does in higher eukaryotes.

By examining growth of the Ubc9-AA strain and others that express partially defective or diminished levels of Ubc9, we determined that yeast can tolerate dramatic reductions in [200~sumoylation levels under normal growth. Whereas a reduction to ~25% of normal sumoylation levels in the Ubc9-AA strain results in no growth defect, the tetracycline-treated Ubc9-TO strain, which harbours ~5% of normal sumoylation, shows a modest growth defect on solid medium. We note that the Ubc9-TO and Ubc9-AA strains derive from different backgrounds (BY4741 and W303a, respectively), and that genetic variations between the strains might have an impact on specific tolerance levels. Nonetheless, these results suggest that somewhere between 75% and 95% of SUMO conjugation events are not required for normal growth, and might rather serve a protective, pre-emptive role in anticipation of stress-inducing changes in the environment. However, reduced sumoylation levels did not impact growth when cells were challenged with osmotic, oxidative, and ethanol stress, all of which can trigger elevated sumoylation in the SUMO stress response (SSR; (Zhou et al. 2004; Lewicki et al. 2015)).

Our observations align with the proposal that the SSR is primarily a consequence of altered transcription genome-wide, which involves a wave of transcription-mediated SUMO conjugation, and suggest that high levels of overall sumoylation do not play a protective role during these stresses (Lewicki et al. 2015). However, further analysis is needed to determine whether elevated sumoylation of specific substrates functions in cellular stress responses. In contrast to these stresses, reduced cellular sumoylation levels did elicit sensitivity to elevated temperatures, particularly in the Ubc9-AA and ubc9-1strains for which higher temperatures are lethal, which is consistent with the finding that sumoylation facilitates heat tolerance in human cells and plants (Yoo et al. 2006; Golebiowski et al. 2009; Zhang et al. 2018). To understand why, among stressors, resistance to high temperatures specifically shows a dependence on sumoylation levels prior to exposure, future studies will be key to determine, at the molecular level, how the modification functions as a general thermoprotectant.

Taken together, our study demonstrates that the bulk of sumoylation events are dispensable for normal growth in yeast but suggests that SUMO modifications serve proactively to protect cells from the effects of elevated temperatures.

MATERIALS AND METHODS

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Repressive Gene Regulation Synchronizes Development With Cellular Metabolism

Justin J. Cassidy et al. (2019-08-08). Northwestern University, Evanston, Illinois | California Institute of Technology, Pasadena, California DOI: 10.1016/j.cell.2019.06.023

HIGHLIGHTS

  • Cellular metabolic rate controls the tempo of development
  • Multiple weak repressors allow GRN dynamics to adjust to a variable tempo
  • Slow metabolism renders individual repressors redundant
  • microRNAs [miRNA] become dispensable for development in the context of slower metabolism

SUMMARY

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.

Keywords, phrases: Drosophila; microRNA; metabolism; development; mathematical modeling; control theory

INTRODUCTION

Animal development occurs over a defined timescale, which is an intrinsic feature of a species and not necessarily determined by external clocks (Ebisuya and Briscoe, 2018). Development occurs via a stereotypic sequence of events involving cell division, growth, movement, apoptosis, polarization, and differentiation. Correct assembly of functional structures depends on synchronization of cell division and differentiation events (Foe, 1989; Sulston et al., 1983). Small variation in timing produces variation in structure that is observed between individuals (Francesconi and Lehner, 2014; Poullet et al., 2016). Abnormal timing can result in structural defects that lead to compromised survival (Moss, 2007). Thus, the rates of various developmental processes must be controlled and coordinated.

Although developmental tempo is a fundamental property of a species, it can vary under different conditions. For example, temperature affects the pace of development in many ectotherms, such as arthropods, nematodes, fish, and reptiles (Atlas, 1935; Davidson, 1944; Kuntz and Eisen, 2014; Zuo et al., 2012). Diet and food intake also affect organismal growth rate and the pace of development for many species, including humans (Arendt, 1997; Brown et al., 2004; Metcalfe and Monaghan, 2001; Pontzer et al., 2016). The interactions between food intake and development are complex and involve hormonal signaling (Bergland et al., 2008; Tang et al., 2011). Finally, cellular metabolism can alter the pace of development. For example, the evolutionarily conserved clk1 gene encodes a mitochondrial enzyme necessary for normal cellular respiration (Felkai et al., 1999), and loss of the clk1 gene in nematodes and mice results in developmental delays (Levavasseur et al., 2001; Nakai et al., 2001; Wong et al., 1995). In Drosophila, restricting glucose consumption by cells slows development (Brogiolo et al., 2001; Layalle et al., 2008; Rulifson et al., 2002; Shingleton et al., 2005). Gillooly et al. (2002) formulated a general quantitative model that relates developmental tempo to organismal mass, cellular metabolic rate, and temperature. Strikingly, the model fits meta-data spanning the major animal phyla, suggesting a universal relationship between metabolism and developmental tempo.

Many developmental processes involve specification of different cell types in a stereotyped sequence. All of these differentiated cell types originate from progenitor cells. The sequence of cell differentiation is driven by changes in the gene expression program within progenitors. Gene regulators, typically transcription factors, are sequentially activated and repressed, resulting in transient periods of increased activity. During these periods, they change gene expression in the progenitors. This coincides with and causes a temporal series of cell fate decisions. Because these regulators frequently interact with one another, the entire cascade constitutes a gene regulatory network (GRN). Such GRNs have been characterized for embryogenesis (Cusanovich et al., 2018; Davidson and Erwin, 2006; Lawrence, 1992), development of the central nervous system (CNS) (Kohwi and Doe, 2013), and development of the sensory nervous system (Cepko, 2014). Because the tempo of development can vary, GRN dynamics must be able to reliably adjust to a variable timing mechanism. Therefore, understanding how these GRNs adapt to a variable timescale is crucial for understanding the mechanisms of animal development.

Phenomenological observations suggest that there are limits to the timescales to which development may adapt. Although broiler chickens have been successfully bred for rapid growth, frequent abnormalities in musculoskeletal development are evident in such breeds (Julian, 2005; Whitehead et al., 2003). Animals (and humans) experience hyper-normal growth rates when they initially experience delayed growth (Arendt, 1997). Such compensatory growth is linked to a variety of developmental and physiological defects (Metcalfe and Monaghan, 2001). Conversely, slowing growth can alleviate defects caused by mutations that impair development. As first noted by Morgan (1915, 1929), morphological phenotypes can be suppressed by limiting the nutrition of mutant animals (Child, 1939; Sang and Burnet, 1963). Likewise, raising animals under lowered temperatures can sometimes suppress the phenotypes of mutations that are not classical temperature sensitive (ts) alleles (Child, 1935; Krafka, 1920; Lewis et al., 1980; Villee, 1943). Collectively, these observations suggest that an unknown mechanism ensures successful developmental outcomes amidst variability in develop mental tempo.

Here, we explored this mechanism. We find that impairing gene repression in GRNs only causes developmental errors when cell metabolism and growth rate are normal. When either energy metabolism or protein synthesis rate is reduced, developmental errors are reduced or even suppressed. We find that this relationship between metabolism and repression is so prevalent that the entire microRNA family becomes less essential for development when metabolism is slowed. Using a general mathematical modeling framework, we show that multiple layers of weak repression render gene expression dynamics independent of variable biochemical rates. When rates are modestly reduced, fewer repressors are needed to ensure normal expression dynamics. We experimentally validate this model prediction by following GRN dynamics in Drosophila. Our findings support a new mechanism whereby layers of gene repression allow development to proceed faster when metabolic conditions allow it. The need for flexible and robust developmental outcomes could provide an evolutionary impetus for the high prevalence of genetic redundancy.

RESULTS

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DISCUSSION

Growth and development are fueled by metabolism. This means that the tempo of development depends on metabolic rate. Thus, the dynamics of developmental gene expression must faithfully adjust to a variable timescale. We have shown that multi-layered weak repression within GRNs plays an unexpected function in synchronizing gene expression dynamics with the variable pace of the developmental program. Multiple repressors are required for accelerated development when metabolism is high, and they become functionally redundant when metabolism is low. Multiple repressors therefore allow reliable development across a broader range of metabolic conditions than tolerated otherwise.

Our model explains long-standing observations linking nutrient limitation to suppression of mutant phenotypes (Morgan, 1915, 1929). Presumably, such mutations cripple regulatory genes acting on developmental GRNs. Our model might also offer an explanation for why animals that undergo above-normal growth exhibit compromised development (Arendt, 1997; Metcalfe and Monaghan, 2001). Wild-type GRNs might function across a limited range of metabolism, with functionality breaking down when metabolism exceeds that range.

Another mechanism to explain phenotype suppression relies on a steady-state and not dynamic perspective of gene expression. Genome-wide gene expression patterns could conceivably change with organismal growth rate. This is the case for chemostat-grown yeast cells, where the expression of 27% of all genes correlates with growth rate (Brauer et al., 2008). Most genes associated with stress response are overexpressed when cells grow at a slow rate (Brauer et al., 2008; Lu et al., 2009). Such stress-responsive expression could modulate global processes such as protein folding and turnover, among others, and attenuate phenotypes when metabolism is slowed (Webb and Brunet, 2014). Indeed, molecular chaperones have been found to affect the penetrance of diverse gene mutations in C. elegans and Drosophila (Casanueva et al., 2012; Rutherford and Lindquist, 1998). However, this steady-state model does not explain why gene expression dynamics are conditionally dependent on the availability of repressors. We found that repression of Yan and Sens expression by microRNAs becomes more redundant when metabolic rates are slowed. Nevertheless, phenotype suppression might be due to a combination of mechanisms, including steady-state stress response and gene expression dynamics.

Our varied analyses suggest that the relationship between metabolism and gene expression dynamics is widespread. We found that the entire family of 466 microRNAs in Drosophila melanogaster become much less essential for development when energy metabolism is slowed. The extensive literature on microRNA function in Drosophila implicates them in practically all facets of the fruit fly’s life (Bushati and Cohen, 2007; Carthew et al., 2017). Various explanations have been provided for why this family of weak repressors has flourished in the animal kingdom, chief among them the idea that they act as buffers for gene expression (Ebert and Sharp, 2012). We now posit that microRNAs also provide a robust means for developmental processes to accommodate fluctuations in metabolism.

Raising animals at lower temperatures can suppress the phenotypes of mutations that are not classical ts alleles (Child, 1935; Krafka, 1920; Lewis et al., 1980; Villee, 1943). Indeed, loss of sens repression by miR-9a has less impact on bristle development when temperature is lowered (Cassidy et al., 2013). Because metabolic rate varies with temperature (Zuo et al., 2012), it is possible that temperature-dependent phenotype suppression may also be attributed to a relaxed requirement for coupling gene expression dynamics to a metabolism-dependent timescale. We explored this notion using our modeling framework, and the results are inconclusive (S.M.B., N.B., and L.A.N.A., unpublished data). We anticipate that error suppression will be weak when temperature-modulated expression dynamics are the sole cause. This is because temperature should affect the rates of both anabolic and catabolic processes involved in gene expression. In contrast, limiting ATP availability or protein translation reduces the rates of anabolic reactions but not all catabolic reactions. This asymmetric effect on different steps in gene expression is a major reason why gene repression becomes less important when ATP availability or protein translation is limited.

Metabolic conditions drive variation of the intrinsic developmental tempo of each species. We have shown that layered weak repression within GRNs enables these fluctuations to occur without causing developmental errors. Metabolic conditions change in both space and time. Perhaps the selective advantage of a reliable developmental outcome amidst variable environmental conditions is a driving force in the evolution of gene regulatory networks.

METHODS

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Media

Slowing metabolic rate can prevent detrimental effects of genetic mutations: Finding appears to be universal across hundreds of tested mutations

Date: July 25, 2019
Source: Northwestern University

Just by slowing their metabolism, mutant fruit flies can go from zero to hero. In a new Northwestern University study, researchers slowed mutant fruit flies’ metabolic rates by 50%, and the expected detrimental effects of many mutations never manifested. After experimentally testing fruit flies’ many different genetic mutations, the researchers found the same result each time.

“When the flies developed at a normal rate, developmental problems occurred,” said Northwestern’s Richard Carthew, who led the experimental research. “When we slowed the rate, developmental problems disappeared. They develop slower and grow slower, but, otherwise, they are normal animals.” “This upends the paradigm of everything we know about development,” added Northwestern’s Luís Amaral, who led the computational research. “We have always thought that if you ‘break’ some genes, there will be serious developmental consequences. It turns out that’s not true for some genes – as long as you also slow the metabolism of the growing organism.”

The research could explain a number of factors, such as why factory-farmed chickens that are bred for hyper growth have more developmental problems or why caloric restriction is linked to longevity. The study will publish on July 25 in the journal Cell. Carthew is a professor of molecular biosciences in Northwestern’s Weinberg College of Arts and Sciences and professor of biochemistry and molecular genetics in the Feinberg School of Medicine. Amaral is the Erastus O. Haven Professor of Chemical and Biological Engineering in Northwestern’s McCormick School of Engineering.

In perhaps the study’s most striking discovery, researchers found that fruit flies – with slowed metabolic rates – could live without any microRNAs, which was previously thought impossible. Found in all plant and animal species, microRNAs play a key role in regulating gene expression. To put it simply: microRNAs control development, physiology and behavior.

“We know from 20 years of research, microRNAs are essential for life. If you didn’t have any microRNAs, you would be dead. Simple as that,” Carthew said. “In our study, we slowed down the metabolism of fruit flies that were not making any microRNAs whatsoever. They survived, they grew and they became normal adults. “Our result concludes that this entire family of gene regulators is not essential,” he added. “All you have to do is slow metabolism by roughly 50%.”

Nobel laureate Thomas Hunt Morgan first noted the connection between diet and genetic mutations in 1915. When he raised mutant fruit flies on limited amounts of poor food, Morgan noticed that some mutations were never expressed. “He thought it was interesting, but he had no explanation,” Carthew said.

Carthew and Amaral now believe the answer is feedback control. Common in biology, engineering, economics and many other fields, feedback control enables complex systems to adjust performance in order to meet a desired response. After completing hundreds of experiments across several years, the Northwestern duo believes that a slower metabolism gives the animals’ systems time to correct errors.

“When you look at all the different proteins and genes that interact within a cell, you can get overwhelmed by all the components and the interactions among them,” Amaral said. “If you are growing fast and something goes wrong, it can be catastrophic. You need these complex networks because they increase redundancy to prevent catastrophe. “But if you are growing slowly, you might not need such a complex system,” he said. “You have more time to adjust to mistakes and react to changes.”

In other words, if you give the system more time, it will eventually get to where it needs to be. Carthew, who is also a member of the Robert H. Lurie Comprehensive Cancer Center of Northwestern University, said this finding could eventually be applied to cancer. “Tumors extremely metabolically active,” he said. “Tumors soak up an enormous amount of energy, which is why cancer patients are often exhausted. We could potentially think about ways to target the metabolism of cancer cells. Maybe by slowing their metabolic rate, we could stop the oncogenic mutations in tumor cells from expressing their cancer phenotype.”

Reference. Justin J Cassidy, Sebastian Bernasek, Rachael Bakker, Ritika Giri, Nicolas Pelaez, Bryan Eder, Anna Bobrowska, Neda Bagheri, Luis A Amaral, Richard W Carthew. “Repressive Gene Regulation Synchronizes Development With Cellular Metabolism.” Cell, 2019