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Antibiotics have dose-dependent effects on exposed bacteria. The medicinal use of antibiotics relies on their growth-inhibitory activities at sufficient concentrations. At subinhibitory concentrations, exposure effects vary widely among different antibiotics and bacteria. Bacillus subtilis responds to bacteriostatic translation inhibitors by mobilizing a population of cells (MOB-Mobilized Bacillus ) to spread across a surface. How B. subtilis regulates the antibiotic-induced mobilization is not known. In this study, we used chloramphenicol to identify regulatory functions that B. subtilis requires to coordinate cell mobilization following subinhibitory exposure. We measured changes in gene expression and metabolism and mapped the results to a network of regulatory proteins that direct the mobile response. Our data reveal that several transcriptional regulators coordinately control the reprogramming of metabolism to support mobilization. The network regulates changes in glycolysis, nucleotide metabolism, and amino acid metabolism that are signature features of the mobilized population. Among the hundreds of genes with changing expression, we identified two, pdhA and pucA , where the magnitudes of their changes in expression, and in the abundance of associated metabolites, reveal hallmark metabolic features of the mobilized population. Using reporters of pdhA and pucA expression, we visualized the separation of major branches of metabolism in different regions of the mobilized population. Our results reveal a regulated response to chloramphenicol exposure that enables a population of bacteria in different metabolic states to mount a coordinated mobile response.

Our understanding of metabolic networks is incomplete, and new enzymatic activities await discovery in well-studied organisms. Mass spectrometric measurement of cellular metabolites reveals compounds inside cells that are unexplained by current maps of metabolic reactions, and existing computational models are unable to account for all activities observed within cells. Additional large-scale genetic and biochemical approaches are required to elucidate metabolic gene function. We have used full-scan mass spectrometry metabolomics of polar small molecules to examine deletion mutants of candidate enzymes in the model yeast Saccharomyces cerevisiae. We report the identification of 25 genes whose deletion results in focal metabolic changes consistent with loss of enzymatic activity and describe the informatic approaches used to enrich for candidate enzymes from uncharacterized open reading frames. Triumphs and pitfalls of metabolic phenotyping screens are discussed, including estimates of the frequency of uncharacterized eukaryotic genes that affect metabolism and key issues to consider when searching for new enzymatic functions in other organisms.

Fluorescent reporter genes have long been used to quantify various cell features such as transcript and protein abundance. Here, we describe a method, reporter synthetic genetic array (R-SGA) analysis, which allows for the simultaneous quantification of any fluorescent protein readout in thousands of yeast strains using an automated pipeline. R-SGA combines a fluorescent reporter system with standard SGA analysis and can be used to examine any array-based strain collection available to the yeast community. This protocol describes the R-SGA methodology for screening different arrays of yeast mutants including the deletion collection, a collection of temperature-sensitive strains for the assessment of essential yeast genes and a collection of inducible overexpression strains. We also present an alternative pipeline for the analysis of R-SGA output strains using flow cytometry of cells in liquid culture. Data normalization for both pipelines is discussed.

Prior to mass spectrometric analysis, cellular small molecules must be extracted and separated from interfering components such as salts and culture medium. To ensure minimal perturbation of metabolism, yeast cells grown in liquid culture are rapidly harvested by filtration as described here. Simultaneous quenching of metabolism and extraction is afforded by immediate immersion in low-temperature organic solvent. Samples prepared using this method are suitable for a range of downstream liquid chromatography-mass spectrometry analyses and are stable in solvent for >1 yr at -80°C., (© 2017 Cold Spring Harbor Laboratory Press.)

L-2-hydroxyglutarate (L-2HG) has emerged as a putative oncometabolite that is capable of inhibiting enzymes involved in metabolism, chromatin modification, and cell differentiation. However, despite the ability of L-2HG to interfere with a broad range of cellular processes, this molecule is often characterized as a metabolic waste product. Here, we demonstrate that Drosophila larvae use the metabolic conditions established by aerobic glycolysis to both synthesize and accumulate high concentrations of L-2HG during normal developmental growth. A majority of the larval L-2HG pool is derived from glucose and dependent on the Drosophila estrogen-related receptor (dERR), which promotes L-2HG synthesis by up-regulating expression of the Drosophila homolog of lactate dehydrogenase (dLdh). We also show that dLDH is both necessary and sufficient for directly synthesizing L-2HG and the Drosophila homolog of L-2-hydroxyglutarate dehydrogenase (dL2HGDH), which encodes the enzyme that breaks down L-2HG, is required for stage-specific degradation of the L-2HG pool. In addition, dLDH also indirectly promotes L-2HG accumulation via synthesis of lactate, which activates a metabolic feed-forward mechanism that inhibits dL2HGDH activity and stabilizes L-2HG levels. Finally, we use a genetic approach to demonstrate that dLDH and L-2HG influence position effect variegation and DNA methylation, suggesting that this compound serves to coordinate glycolytic flux with epigenetic modifications. Overall, our studies demonstrate that growing animal tissues synthesize L-2HG in a controlled manner, reveal a mechanism that coordinates glucose catabolism with L-2HG synthesis, and establish the fly as a unique model system for studying the endogenous functions of L-2HG during cell growth and proliferation., Competing Interests: The authors declare no conflict of interest.

In yeast, cell size is normally tightly linked to cell cycle progression. Centrifugal elutriation is a method that fractionates cells based on the physical properties of cell size-fluid drag and buoyant density. Using a specially modified centrifuge and rotor system, cells can be physically separated into one or more cohorts of similar size and therefore cell cycle position. Small G 1 daughters are collected first, followed by successively larger cells. Elutriated populations can be analyzed immediately or can be returned to medium and permitted to synchronously progress through the cell cycle. This protocol describes two different elutriation methods. In the first, one or more fractions of synchronized cells are obtained from an asynchronous starting population, reincubated, and followed prospectively across a time series. In the second, an asynchronous starting population is separated into multiple fractions of similarly sized cells, and each cohort of similarly sized cells can be analyzed separately without further growth., (© 2017 Cold Spring Harbor Laboratory Press.)

Like other eukaryotes, budding yeast temporally separate cell growth and division. DNA synthesis is distinct from chromosome segregation. Storage carbohydrates are accumulated slowly and then rapidly liquidated once per cycle. Cyclin-dependent kinase associates with multiple different transcriptionally and posttranslationally regulated cyclins to drive the cell cycle. These and other crucial events of cellular growth and division are limited to narrow windows of the cell cycle. Many experiments in the yeast laboratory treat a culture of cells as a homogeneous mixture. Measurements of asynchronous cultures are, however, confounded by the presence of cells in various cell cycle stages; measuring a population average in unsynchronized cells provides at best a decreased signal and at worst an artifactual result. A number of experimentally tractable methods have been developed to generate populations of yeast cells that are synchronized with respect to cell cycle phase. Robust methods for determining cell cycle position have also been developed. These methods are introduced here., (© 2017 Cold Spring Harbor Laboratory Press.)

DNA synthesis is one of the landmark events in the cell cycle: G 1 cells have one copy of the genome, S phase cells are actively engaged in DNA synthesis, and G 2 cells have twice as much nuclear DNA as G 1 cells. Cellular DNA content can be measured by staining with a fluorescent dye followed by a flow-cytometric readout. This method provides a quantitative measurement of cell cycle position on a cell-by-cell basis at high speed. Using flow cytometry, tens of thousands of single-cell measurements can be generated in a few seconds. This protocol details staining of cells of the budding yeast Saccharomyces cerevisiae for flow cytometry using Sytox Green dye in a method that can be scaled widely-from one sample to many thousands and operating on inputs ranging from 1 million to more than 100 million cells. Flow cytometry is preferred over light microscopy or Coulter analyses for the analysis of the cell cycle as DNA content and cell cycle position are being directly measured., (© 2017 Cold Spring Harbor Laboratory Press.)

The cell cycle of budding yeast can be arrested at specific positions by different genetic and chemical methods. These arrests enable study of cell cycle phase-specific phenotypes that would be missed during examination of asynchronous cultures. Some methods for arrest are reversible, with kinetics that enable release of cells back into a synchronous cycling state. Benefits of chemical and genetic methods include scalability across a large range of culture sizes from a few milliliters to many liters, ease of execution, the absence of specific equipment requirements, and synchronization and release of the entire culture. Of note, cell growth and division are decoupled during arrest and block-release experiments. Cells will continue transcription, translation, and accumulation of protein while arrested. If allowed to reenter the cell cycle, cells will do so as a population of mixed, larger-than-normal cells. Despite this important caveat, many aspects of budding yeast physiology are accessible using these simple chemical and genetic tools. Described here are methods for the block and release of cells in G 1 phase and at the M/G 1 transition using α-factor mating pheromone and the temperature-sensitive cdc15-2 allele, respectively, in addition to methods for arresting the cell cycle in early S phase and at G 2 /M by using hydroxyurea and nocodazole, respectively., (© 2017 Cold Spring Harbor Laboratory Press.)

Histone demethylation by Jumonji-family proteins is coupled with the decarboxylation of α-ketoglutarate (αKG) to yield succinate, prompting hypotheses that their activities are responsive to levels of these metabolites in the cell. Consistent with this paradigm we show here that the Saccharomyces cerevisiae Jumonji demethylase Jhd2 opposes the accumulation of H3K4me3 in fermenting cells only when they are nutritionally manipulated to contain an elevated αKG/succinate ratio. We also find that Jhd2 opposes H3K4me3 in respiratory cells that do not exhibit such an elevated αKG/succinate ratio. While jhd2∆ caused only limited gene expression defects in fermenting cells, transcript profiling and physiological measurements show that JHD2 restricts mitochondrial respiratory capacity in cells grown in non-fermentable carbon in an H3K4me-dependent manner. In association with these phenotypes, we find that JHD2 limits yeast proliferative capacity under physiologically challenging conditions as measured by both replicative lifespan and colony growth on non-fermentable carbon. JHD2's impact on nutrient response may reflect an ancestral role of its gene family in mediating mitochondrial regulation.

Genetically engineered mouse models (GEMMs) of cancer are increasingly being used to assess putative driver mutations identified by large-scale sequencing of human cancer genomes. To accurately interpret experiments that introduce additional mutations, an understanding of the somatic genetic profile and evolution of GEMM tumors is necessary. Here, we performed whole-exome sequencing of tumors from three GEMMs of lung adenocarcinoma driven by mutant epidermal growth factor receptor (EGFR), mutant Kirsten rat sarcoma viral oncogene homolog (Kras), or overexpression of MYC proto-oncogene. Tumors from EGFR- and Kras-driven models exhibited, respectively, 0.02 and 0.07 nonsynonymous mutations per megabase, a dramatically lower average mutational frequency than observed in human lung adenocarcinomas. Tumors from models driven by strong cancer drivers (mutant EGFR and Kras) harbored few mutations in known cancer genes, whereas tumors driven by MYC, a weaker initiating oncogene in the murine lung, acquired recurrent clonal oncogenic Kras mutations. In addition, although EGFR- and Kras-driven models both exhibited recurrent whole-chromosome DNA copy number alterations, the specific chromosomes altered by gain or loss were different in each model. These data demonstrate that GEMM tumors exhibit relatively simple somatic genotypes compared with human cancers of a similar type, making these autochthonous model systems useful for additive engineering approaches to assess the potential of novel mutations on tumorigenesis, cancer progression, and drug sensitivity., Competing Interests: The authors declare no conflict of interest.

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell., (Copyright © 2016, American Association for the Advancement of Science.)

The genetic basis of heritable traits has been studied for decades. Although recent mapping efforts have elucidated genetic determinants of transcript levels, mapping of protein abundance has lagged. Here, we analyze levels of 4084 GFP-tagged yeast proteins in the progeny of a cross between a laboratory and a wild strain using flow cytometry and high-content microscopy. The genotype of trans variants contributed little to protein level variation between individual cells but explained >50% of the variance in the population's average protein abundance for half of the GFP fusions tested. To map trans-acting factors responsible, we performed flow sorting and bulk segregant analysis of 25 proteins, finding a median of five protein quantitative trait loci (pQTLs) per GFP fusion. Further, we find that cis-acting variants predominate; the genotype of a gene and its surrounding region had a large effect on protein level six times more frequently than the rest of the genome combined. We present evidence for both shared and independent genetic control of transcript and protein abundance: More than half of the expression QTLs (eQTLs) contribute to changes in protein levels of regulated genes, but several pQTLs do not affect their cognate transcript levels. Allele replacements of genes known to underlie trans eQTL hotspots confirmed the correlation of effects on mRNA and protein levels. This study represents the first genome-scale measurement of genetic contribution to protein levels in single cells and populations, identifies more than a hundred trans pQTLs, and validates the propagation of effects associated with transcript variation to protein abundance., (© 2014 Parts et al.; Published by Cold Spring Harbor Laboratory Press.)

Diet greatly influences gene expression and physiology. In mammals, elucidating the effects and mechanisms of individual nutrients is challenging due to the complexity of both the animal and its diet. Here, we used an interspecies systems biology approach with Caenorhabditis elegans and two of its bacterial diets, Escherichia coli and Comamonas aquatica, to identify metabolites that affect the animal's gene expression and physiology. We identify vitamin B12 as the major dilutable metabolite provided by Comamonas aq. that regulates gene expression, accelerates development, and reduces fertility but does not affect lifespan. We find that vitamin B12 has a dual role in the animal: it affects development and fertility via the methionine/S-Adenosylmethionine (SAM) cycle and breaks down the short-chain fatty acid propionic acid, preventing its toxic buildup. Our interspecies systems biology approach provides a paradigm for understanding complex interactions between diet and physiology., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Regulation of cell growth is a fundamental process in development and disease that integrates a vast array of extra- and intracellular information. A central player in this process is RNA polymerase I (Pol I), which transcribes ribosomal RNA (rRNA) genes in the nucleolus. Rapidly growing cancer cells are characterized by increased Pol I-mediated transcription and, consequently, nucleolar hypertrophy. To map the genetic network underlying the regulation of nucleolar size and of Pol I-mediated transcription, we performed comparative, genome-wide loss-of-function analyses of nucleolar size in Saccharomyces cerevisiae and Drosophila melanogaster coupled with mass spectrometry-based analyses of the ribosomal DNA (rDNA) promoter. With this approach, we identified a set of conserved and nonconserved molecular complexes that control nucleolar size. Furthermore, we characterized a direct role of the histone information regulator (HIR) complex in repressing rRNA transcription in yeast. Our study provides a full-genome, cross-species analysis of a nuclear subcompartment and shows that this approach can identify conserved molecular modules.

DNA double-strand break (DSB) repair pathway choice is governed by the opposing activities of 53BP1 and BRCA1. 53BP1 stimulates nonhomologous end joining (NHEJ), whereas BRCA1 promotes end resection and homologous recombination (HR). Here we show that 53BP1 is an inhibitor of BRCA1 accumulation at DSB sites, specifically in the G1 phase of the cell cycle. ATM-dependent phosphorylation of 53BP1 physically recruits RIF1 to DSB sites, and we identify RIF1 as the critical effector of 53BP1 during DSB repair. Remarkably, RIF1 accumulation at DSB sites is strongly antagonized by BRCA1 and its interacting partner CtIP. Lastly, we show that depletion of RIF1 is able to restore end resection and RAD51 loading in BRCA1-depleted cells. This work therefore identifies a cell cycle-regulated circuit, underpinned by RIF1 and BRCA1, that governs DSB repair pathway choice to ensure that NHEJ dominates in G1 and HR is favored from S phase onward., (Copyright © 2013 Elsevier Inc. All rights reserved.)

A report on the 13th International Conference on Systems Biology, held in Toronto, Ontario, Canada, 19-23 August 2012.

In S. pombe, about 5% of genes are meiosis-specific and accumulate little or no mRNA during vegetative growth. Here we use Affymetrix tiling arrays to characterize transcripts in vegetative and meiotic cells. In vegetative cells, many meiotic genes, especially those induced in mid-meiosis, have abundant antisense transcripts. Disruption of the antisense transcription of three of these mid-meiotic genes allowed vegetative sense transcription. These results suggest that antisense transcription represses sense transcription of meiotic genes in vegetative cells. Although the mechanism(s) of antisense mediated transcription repression need to be further explored, our data indicates that RNAi machinery is not required for repression. Previously, we and others used non-strand specific methods to study splicing regulation of meiotic genes and concluded that 28 mid-meiotic genes are spliced only in meiosis. We now demonstrate that the "unspliced" signal in vegetative cells comes from the antisense RNA, not from unspliced sense RNA, and we argue against the idea that splicing regulates these mid-meiotic genes. Most of these mid-meiotic genes are induced in mid-meiosis by the forkhead transcription factor Mei4. Interestingly, deletion of a different forkhead transcription factor, Fkh2, allows low levels of sense expression of some mid-meiotic genes in vegetative cells. We propose that vegetative expression of mid-meiotic genes is repressed at least two independent ways: antisense transcription and Fkh2 repression.

The amino sugar N-acetylglucosamine (GlcNAc) is known to be an important structural component of cells from bacteria to humans, but its roles in cell signaling are less well understood. GlcNAc induces two pathways in the human fungal pathogen Candida albicans. One activates cyclic AMP (cAMP) signaling, which stimulates the formation of hyphal cells and the expression of virulence genes, and the other pathway induces genes needed to catabolize GlcNAc. Microarray analysis of gene expression was carried out under four different conditions in order to characterize the transcriptional changes induced by GlcNAc. The most highly induced genes include those that encode a GlcNAc transporter (NGT1) and the GlcNAc catabolic enzymes (HXK1, DAC1, and NAG1). GlcNAc also activated most of the genes whose expression is increased when cells are triggered with other stimuli to form hyphae. Surprisingly, GlcNAc also induced a subset of genes that are regulated by galactose (GAL1, GAL7, and GAL10), which may be due to cross talk between signaling pathways. A novel GlcNAc-induced gene, GIG1, which is not essential for GlcNAc catabolism or the induction of hyphae, was identified. However, a Gig1-green fluorescent protein (GFP) fusion protein was specifically induced by GlcNAc, and not by other sugars. Gig1-GFP localized to the cytoplasm, where GlcNAc metabolism occurs. Significantly, a gig1Δ mutant displayed increased resistance to nikkomycin Z, which inhibits chitin synthase from converting UDP-GlcNAc into cell wall chitin. Gig1 is highly conserved in fungi, especially those that contain GlcNAc catabolic genes. These results implicate Gig1 in GlcNAc metabolism.

In budding yeast, asymmetric cell division yields a larger mother and a smaller daughter cell, which transcribe different genes due to the daughter-specific transcription factors Ace2 and Ash1. Cell size control at the Start checkpoint has long been considered to be a main regulator of the length of the G1 phase of the cell cycle, resulting in longer G1 in the smaller daughter cells. Our recent data confirmed this concept using quantitative time-lapse microscopy. However, it has been proposed that daughter-specific, Ace2-dependent repression of expression of the G1 cyclin CLN3 had a dominant role in delaying daughters in G1. We wanted to reconcile these two divergent perspectives on the origin of long daughter G1 times. We quantified size control using single-cell time-lapse imaging of fluorescently labeled budding yeast, in the presence or absence of the daughter-specific transcriptional regulators Ace2 and Ash1. Ace2 and Ash1 are not required for efficient size control, but they shift the domain of efficient size control to larger cell size, thus increasing cell size requirement for Start in daughters. Microarray and chromatin immunoprecipitation experiments show that Ace2 and Ash1 are direct transcriptional regulators of the G1 cyclin gene CLN3. Quantification of cell size control in cells expressing titrated levels of Cln3 from ectopic promoters, and from cells with mutated Ace2 and Ash1 sites in the CLN3 promoter, showed that regulation of CLN3 expression by Ace2 and Ash1 can account for the differential regulation of Start in response to cell size in mothers and daughters. We show how daughter-specific transcriptional programs can interact with intrinsic cell size control to differentially regulate Start in mother and daughter cells. This work demonstrates mechanistically how asymmetric localization of cell fate determinants results in cell-type-specific regulation of the cell cycle., Competing Interests: The authors have declared that no competing interests exist.