Gene Transcription as a Limiting Factor in Protein Production and Cell Growth

Noise robustness and metabolic load determine the principles of central dogma regulation

The processes of gene expression are inherently stochastic, even for essential genes required for growth. How does the cell maximize fitness in light of noise? To answer this question, we build a mathematical model to explore the trade-off between metabolic load and growth robustness. The model predicts novel principles of central dogma regulation: Optimal protein expression levels for many genes are in vast overabundance. Essential genes are transcribed above a lower limit of one message per cell cycle. Gene expression is achieved by load balancing between transcription and translation. We present evidence that each of these novel regulatory principles is observed. These results reveal that robustness and metabolic load determine the global regulatory principles that govern central dogma processes, and these principles have broad implications for cellular function.

How total mRNA influences cell growth

Experimental observations tracing back to the 1960s imply that ribosome quantities play a prominent role in determining a cell's growth. Nevertheless, in biologically relevant scenarios, growth can also be influenced by the levels of mRNA and RNA polymerase. Here, we construct a quantitative model of biosynthesis providing testable scenarios for these situations. The model explores a theoretically motivated regime where RNA polymerases compete for genes and ribosomes for transcripts and gives general expressions relating growth rate, mRNA concentrations, ribosome, and RNA polymerase levels. On general grounds, the model predicts how the fraction of ribosomes in the proteome depends on total mRNA concentration and inspects an underexplored regime in which the trade-off between transcript levels and ribosome abundances sets the cellular growth rate. In particular, we show that the model predicts and clarifies three important experimental observations, in budding yeast and Escherichia coli bacteria: i) that the growth-rate cost of unneeded protein expression can be affected by mRNA levels, ii) that resource optimization leads to decreasing trends in mRNA levels at slow growth, and iii) that ribosome allocation may increase, stay constant, or decrease, in response to transcription-inhibiting antibiotics. Since the data indicate that a regime of joint limitation may apply in physiological conditions and not only to perturbations, we speculate that this regime is likely self-imposed.

Transcript accumulation rates in the early Caenorhabditis elegans embryo

Dynamic transcriptional changes are widespread in rapidly dividing developing embryos when cell fate decisions are made quickly. The Caenorhabditis elegans embryo overcomes these constraints partly through the rapid production of high levels of transcription factor mRNAs. Transcript accumulation rates for some developmental genes are known at single-cell resolution, but genome-scale measurements are lacking. We estimate zygotic mRNA accumulation rates from single-cell RNA sequencing data calibrated with single-molecule transcript imaging. Rapid transcription is common in the early C. elegans embryo with rates highest soon after zygotic transcription begins. High-rate genes are enriched for recently duplicated cell-fate regulators and share common genomic features. We identify core promoter elements associated with high rate and measure their contributions for two early endomesodermal genes, ceh-51 and sdz-31. Individual motifs modestly affect accumulation rates, suggesting multifactorial control. These results are a step toward estimating absolute transcription kinetics and understanding how transcript dosage drives developmental decisions.

MicroRNAs as Targets for Cancer Diagnosis: Interests and Limitations

MicroRNAs are small RNAs with ability to attach to the large number of RNA that regulate gene expression on post-transcriptional level via inhibition or degradation of specific mRNAs. MiRNAs in cells are the primary regulators of functions such as cell growth, differentiation, and apoptosis and considerably influence cell function. The expression levels of microRNAs change in human diseases, including cancer. These changes highlight their essential role in cancer pathogenesis. Ubiquitous irregular expression profiles of miRNAs have been detected in various human cancers using genome-wide identification techniques, which are emerging as novel diagnostic and prognostic cancer biomarkers of high specificity and sensitivity. The measurable miRNAs with enhanced stability in blood, tissues, and other body fluids provide a comprehensive source of miRNA-dependent biomarkers for human cancers. The leading role of miRNAs as potential biomarkers in human cancers is discussed in this article. In addition, the interests and difficulties of miRNAs as biomarkers have been explored.

Scaling of nuclear numbers and their spatial arrangement in skeletal muscle cell size regulation

Many cells display considerable functional plasticity and depend on the regulation of numerous organelles and macromolecules for their maintenance. In large cells, organelles also need to be carefully distributed to supply the cell with essential resources and regulate intracellular activities. Having multiple copies of the largest eukaryotic organelle, the nucleus, epitomizes the importance of scaling gene products to large cytoplasmic volumes in skeletal muscle fibers. Scaling of intracellular constituents within mammalian muscle fibers is, however, poorly understood, but according to the myonuclear domain hypothesis, a single nucleus supports a finite amount of cytoplasm and is thus postulated to act autonomously, causing the nuclear number to be commensurate with fiber volume. In addition, the orderly peripheral distribution of myonuclei is a hallmark of normal cell physiology, as nuclear mispositioning is associated with impaired muscle function. Because underlying structures of complex cell behaviors are commonly formalized by scaling laws and thus emphasize emerging principles of size regulation, the work presented herein offers more of a unified conceptual platform based on principles from physics, chemistry, geometry, and biology to explore cell size-dependent correlations of the largest mammalian cell by means of scaling.

Scaling of biosynthesis and metabolism with cell size

Cells adopt a size that is optimal for their function, and pushing them beyond this limit can cause cell aging and death by senescence or reduce proliferative potential. However, by increasing their genome copy number (ploidy), cells can increase their size dramatically and homeostatically maintain physiological properties such as biosynthesis rate. Recent studies investigating the relationship between cell size and rates of biosynthesis and metabolism under normal, polyploid, and pathological conditions are revealing new insights into how cells attain the best function or fitness for their size by tuning processes including transcription, translation, and mitochondrial respiration. A new frontier is to connect single-cell scaling relationships with tissue and whole-organism physiology, which promises to reveal molecular and evolutionary principles underlying the astonishing diversity of size observed across the tree of life.

The histone chaperone FACT: a guardian of chromatin structure integrity

The identification of FACT as a histone chaperone enabling transcription through chromatin in vitro has strongly shaped how its roles are envisioned. However, FACT has been implicated in essentially all aspects of chromatin biology, from transcription to DNA replication, DNA repair, and chromosome segregation. In this review, we focus on recent literature describing the role and mechanisms of FACT during transcription. We highlight the prime importance of FACT in preserving chromatin integrity during transcription and challenge its role as an elongation factor. We also review evidence for FACT's role as a cell-type/gene-specificregulator of gene expression and briefly summarize current efforts at using FACT inhibition as an anti-cancerstrategy.

Natural variation in the consequences of gene overexpression and its implications for evolutionary trajectories

Copy number variation through gene or chromosome amplification provides a route for rapid phenotypic variation and supports the long-term evolution of gene functions. Although the evolutionary importance of copy-number variation is known, little is understood about how genetic background influences its tolerance. Here, we measured fitness costs of over 4000 overexpressed genes in 15 Saccharomyces cerevisiae strains representing different lineages, to explore natural variation in tolerating gene overexpression (OE). Strain-specific effects dominated the fitness costs of gene OE. We report global differences in the consequences of gene OE, independent of the amplified gene, as well as gene-specific effects that were dependent on the genetic background. Natural variation in the response to gene OE could be explained by several models, including strain-specific physiological differences, resource limitations, and regulatory sensitivities. This work provides new insight on how genetic background influences tolerance to gene amplification and the evolutionary trajectories accessible to different backgrounds.

Coordination of transcription and processing of tRNA

Coordination of transcription and processing of RNA is a basic principle in regulation of gene expression in eukaryotes. In the case of mRNA, coordination is primarily founded on a co-transcriptional processing mechanism by which a nascent precursor mRNA undergoes maturation via cleavage and modification by the transcription machinery. A similar mechanism controls the biosynthesis of rRNA. However, the coordination of transcription and processing of tRNA, a rather short transcript, remains unknown. Here, we present a model for high molecular weight initiation complexes of human RNA polymerase III that assemble on tRNA genes and process precursor transcripts to mature forms. These multifunctional initiation complexes may support co-transcriptional processing, such as the removal of the 5' leader of precursor tRNA by RNase P. Based on this model, maturation of tRNA is predetermined prior to transcription initiation.