MOB rules: Antibiotic Exposure Reprograms Metabolism to Mobilize Bacillus subtilis in Competitive Interactions.

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.

Fitness and Productivity Increase with Ecotypic Diversity among Escherichia coli Strains That Coevolved in a Simple, Constant Environment.

The productivity of a biological community often correlates with its diversity. In the microbial world this phenomenon can sometimes be explained by positive, density-dependent interactions such as cross-feeding and syntrophy. These metabolic interactions help account for the astonishing variety of microbial life and drive many of the biogeochemical cycles without which life as we know it could not exist. While it is difficult to recapitulate experimentally how these interactions evolved among multiple taxa, we can explore in the laboratory how they arise within one. These experiments provide insight into how different bacterial ecotypes evolve and from these, possibly new "species." We have previously shown that in a simple, constant environment a single clone of Escherichia coli can give rise to a consortium of genetically and phenotypically differentiated strains, in effect, a set of ecotypes, that coexist by cross-feeding. We marked these different ecotypes and their shared ancestor by integrating fluorescent protein into their genomes and then used flow cytometry to show that each evolved strain is more fit than the shared ancestor, that pairs of evolved strains are fitter still, and that the entire consortium is the fittest of all. We further demonstrate that the rank order of fitness values agrees with estimates of yield, indicating that an experimentally evolved consortium more efficiently converts primary and secondary resources to offspring than its ancestor or any member acting in isolation.IMPORTANCE Polymicrobial consortia occur in both environmental and clinical settings. In many cases, diversity and productivity correlate in these consortia, especially when sustained by positive, density-dependent interactions. However, the evolutionary history of such entities is typically obscure, making it difficult to establish the relative fitness of consortium partners and to use those data to illuminate the diversity-productivity relationship. Here, we dissect an Escherichia coli consortium that evolved under continuous glucose limitation in the laboratory from a single common ancestor. We show that a partnership consisting of cross-feeding ecotypes is better able to secure primary and secondary resources and to convert those resources to offspring than the ancestral clone. Such interactions may be a prelude to a special form of syntrophy and are likely determinants of microbial community structure in nature, including those having clinical significance such as chronic infections.

Diverse conditions support near-zero growth in yeast: Implications for the study of cell lifespan.

Baker's yeast has a finite lifespan and ages in two ways: a mother cell can only divide so many times (its replicative lifespan), and a non-dividing cell can only live so long (its chronological lifespan). Wild and laboratory yeast strains exhibit natural variation for each type of lifespan, and the genetic basis for this variation has been generalized to other eukaryotes, including metazoans. To date, yeast chronological lifespan has chiefly been studied in relation to the rate and mode of functional decline among non-dividing cells in nutrient-depleted batch culture. However, this culture method does not accurately capture two major classes of long-lived metazoan cells: cells that are terminally differentiated and metabolically active for periods that approximate animal lifespan (e.g. cardiac myocytes), and cells that are pluripotent and metabolically quiescent (e.g. stem cells). Here, we consider alternative ways of cultivating Saccharomyces cerevisiae so that these different metabolic states can be explored in non-dividing cells: (i) yeast cultured as giant colonies on semi-solid agar, (ii) yeast cultured in retentostats and provided sufficient nutrients to meet minimal energy requirements, and (iii) yeast encapsulated in a semisolid matrix and fed ad libitum in bioreactors. We review the physiology of yeast cultured under each of these conditions, and explore their potential to provide unique insights into determinants of chronological lifespan in the cells of higher eukaryotes.

Functional genetic discovery of enzymes using full-scan mass spectrometry metabolomics 1.

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.

Reporter-Based Synthetic Genetic Array Analysis: A Functional Genomics Approach for Investigating Transcript or Protein Abundance Using Fluorescent Proteins in Saccharomyces cerevisiae.

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.

Metabolite Extraction from Saccharomyces cerevisiae for Liquid Chromatography-Mass Spectrometry.

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.

Drosophila larvae synthesize the putative oncometabolite L-2-hydroxyglutarate during normal developmental growth.

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.

Synchronization and Arrest of the Budding Yeast Cell Cycle Using Chemical and Genetic Methods.

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 G1 phase and at the M/G1 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 G2/M by using hydroxyurea and nocodazole, respectively.

Synchronization of Budding Yeast by Centrifugal Elutriation.

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 G1 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.

Analysis of the Budding Yeast Cell Cycle by Flow Cytometry.

DNA synthesis is one of the landmark events in the cell cycle: G1 cells have one copy of the genome, S phase cells are actively engaged in DNA synthesis, and G2 cells have twice as much nuclear DNA as G1 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.

Methods for Synchronization and Analysis of the Budding Yeast Cell Cycle.

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.

Mitochondrial control through nutritionally regulated global histone H3 lysine-4 demethylation.

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.

A global genetic interaction network maps a wiring diagram of cellular function.

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.

Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma.

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.

Cell cycle-regulated oscillator coordinates core histone gene transcription through histone acetylation.

DNA replication occurs during the synthetic (S) phase of the eukaryotic cell cycle and features a dramatic induction of histone gene expression for concomitant chromatin assembly. Ectopic production of core histones outside of S phase is toxic, underscoring the critical importance of regulatory pathways that ensure proper expression of histone genes. Several regulators of histone gene expression in the budding yeast Saccharomyces cerevisiae are known, yet the key oscillator responsible for restricting gene expression to S phase has remained elusive. Here, we show that suppressor of Ty (Spt)10, a putative histone acetyltransferase, and its binding partner Spt21 are key determinants of S-phase-specific histone gene expression. We show that Spt21 abundance is restricted to S phase in part by anaphase promoting complex Cdc20-homologue 1 (APC(Cdh1)) and that it is recruited to histone gene promoters in S phase by Spt10. There, Spt21-Spt10 enables the recruitment of a cascade of regulators, including histone chaperones and the histone-acetyltransferase general control nonderepressible (Gcn) 5, which we hypothesize lead to histone acetylation and consequent transcription activation.

Heritability and genetic basis of protein level variation in an outbred population.

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.

Interspecies systems biology uncovers metabolites affecting C. elegans gene expression and life history traits.

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.