Identity and function of a large gene network underlying mutagenic repair of DNA breaks

Metabolic therapy: a new paradigm for managing malignant brain cancer

Little progress has been made in the long-term management of glioblastoma multiforme (GBM), considered among the most lethal of brain cancers. Cytotoxic chemotherapy, steroids, and high-dose radiation are generally used as the standard of care for GBM. These procedures can create a tumor microenvironment rich in glucose and glutamine. Glucose and glutamine are suggested to facilitate tumor progression. Recent evidence suggests that many GBMs are infected with cytomegalovirus, which could further enhance glucose and glutamine metabolism in the tumor cells. Emerging evidence also suggests that neoplastic macrophages/microglia, arising through possible fusion hybridization, can comprise an invasive cell subpopulation within GBM. Glucose and glutamine are major fuels for myeloid cells, as well as for the more rapidly proliferating cancer stem cells. Therapies that increase inflammation and energy metabolites in the GBM microenvironment can enhance tumor progression. In contrast to current GBM therapies, metabolic therapy is designed to target the metabolic malady common to all tumor cells (aerobic fermentation), while enhancing the health and vitality of normal brain cells and the entire body. The calorie restricted ketogenic diet (KD-R) is an anti-angiogenic, anti-inflammatory and pro-apoptotic metabolic therapy that also reduces fermentable fuels in the tumor microenvironment. Metabolic therapy, as an alternative to the standard of care, has the potential to improve outcome for patients with GBM and other malignant brain cancers.

Escherichia coli genes and pathways involved in surviving extreme exposure to ionizing radiation

To further an improved understanding of the mechanisms used by bacterial cells to survive extreme exposure to ionizing radiation (IR), we broadly screened nonessential Escherichia coli genes for those involved in IR resistance by using transposon-directed insertion sequencing (TraDIS). Forty-six genes were identified, most of which become essential upon heavy IR exposure. Most of these were subjected to direct validation. The results reinforced the notion that survival after high doses of ionizing radiation does not depend on a single mechanism or process, but instead is multifaceted. Many identified genes affect either DNA repair or the cellular response to oxidative damage. However, contributions by genes involved in cell wall structure/function, cell division, and intermediary metabolism were also evident. About half of the identified genes have not previously been associated with IR resistance or recovery from IR exposure, including eight genes of unknown function.

Was low CO2 a driving force of C4 evolution: Arabidopsis responses to long-term low CO2 stress

The responses of long-term growth of plants under elevated CO2 have been studied extensively. Comparatively, the responses of plants to subambient CO2 concentrations have not been well studied. This study aims to investigate the responses of the model C3 plant, Arabidopsis thaliana, to low CO2 at the molecular level. Results showed that low CO2 dramatically decreased biomass productivity, together with delayed flowering and increased stomatal density. Furthermore, alteration of thylakoid stacking in both bundle sheath and mesophyll cells, upregulation of PEPC and PEPC-K together with altered expression of a number of regulators known involved in photosynthesis development were observed. These responses to low CO2 are discussed with regard to the fitness of C3 plants under low CO2. This work also briefly discusses the relevance of the data to C4 photosynthesis evolution.

Prediction and redesign of protein-protein interactions

Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function - those mediated by protein-protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI.

Specificity determinants for autoproteolysis of LexA, a key regulator of bacterial SOS mutagenesis

Bacteria utilize the tightly regulated stress response (SOS) pathway to respond to a variety of genotoxic agents, including antimicrobials. Activation of the SOS response is regulated by a key repressor-protease, LexA, which undergoes autoproteolysis in the setting of stress, resulting in derepression of SOS genes. Remarkably, genetic inactivation of LexA’s self-cleavage activity significantly decreases acquired antibiotic resistance in infection models and renders bacteria hypersensitive to traditional antibiotics, suggesting that a mechanistic study of LexA could help inform its viability as a novel target for combating acquired drug resistance. Despite structural insights into LexA, a detailed knowledge of the enzyme’s protease specificity is lacking. Here, we employ saturation and positional scanning mutagenesis on LexA’s internal cleavage region to analyze >140 mutants and generate a comprehensive specificity profile of LexA from the human pathogen Pseudomonas aeruginosa (LexA_Pa). We find that the LexA_Pa active site possesses a unique mode of substrate recognition. Positions P1–P3 prefer small hydrophobic residues that suggest specific contacts with the active site, while positions P5 and P1′ show a preference for flexible glycine residues that may facilitate the conformational change that permits autoproteolysis. We further show that stabilizing the β-turn within the cleavage region enhances LexA autoproteolytic activity. Finally, we identify permissive positions flanking the scissile bond (P4 and P2′) that are tolerant to extensive mutagenesis. Our studies shed light on the active site architecture of the LexA autoprotease and provide insights that may inform the design of probes of the SOS pathway.

Medicine. Combating evolution to fight disease

Molecular mechanisms that generate biological diversity are rewriting ideas about how evolution proceeds, with implications for treating disease.

sigmaS, a major player in the response to environmental stresses in Escherichia coli: role, regulation and mechanisms of promoter recognition

Bacterial cells often face hostile environmental conditions, to which they adapt by activation of stress responses. In Escherichia coli, environmental stresses resulting in significant reduction in growth rate stimulate the expression of the rpoS gene, encoding the alternative σ factor σ(S). The σ(S) protein associates with RNA polymerase, and through transcription of genes belonging to the rpoS regulon allows the activation of a 'general stress response', which protects the bacterial cell from harmful environmental conditions. Each step of this process is finely tuned in order to cater to the needs of the bacterial cell: in particular, selective promoter recognition by σ(S) is achieved through small deviations from a common consensus DNA sequence for both σ(S) and the housekeeping σ(70). Recognition of specific DNA elements by σ(S) is integrated with the effects of environmental signals and the interaction with regulatory proteins, in what represents a fascinating example of multifactorial regulation of gene expression. In this report, we discuss the function of the rpoS gene in the general stress response, and review the current knowledge on regulation of rpoS expression and on promoter recognition by σ(S).

Monitoring intraspecies competition in a bacterial cell population by cocultivation of fluorescently labelled strains

Many microorganisms such as bacteria proliferate extremely fast and the populations may reach high cell densities. Small fractions of cells in a population always have accumulated mutations that are either detrimental or beneficial for the cell. If the fitness effect of a mutation provides the subpopulation with a strong selective growth advantage, the individuals of this subpopulation may rapidly outcompete and even completely eliminate their immediate fellows. Thus, small genetic changes and selection-driven accumulation of cells that have acquired beneficial mutations may lead to a complete shift of the genotype of a cell population. Here we present a procedure to monitor the rapid clonal expansion and elimination of beneficial and detrimental mutations, respectively, in a bacterial cell population over time by cocultivation of fluorescently labeled individuals of the Gram-positive model bacterium Bacillus subtilis. The method is easy to perform and very illustrative to display intraspecies competition among the individuals in a bacterial cell population.

Microbial persistence and the road to drug resistance

Microbial drug persistence is a widespread phenomenon in which a subpopulation of microorganisms is able to survive antimicrobial treatment without acquiring resistance-conferring genetic changes. Microbial persisters can cause recurrent or intractable infections, and, like resistant mutants, they carry an increasing clinical burden. In contrast to heritable drug resistance, however, the biology of persistence is only beginning to be unraveled. Persisters have traditionally been thought of as metabolically dormant, nondividing cells. As discussed in this review, increasing evidence suggests that persistence is in fact an actively maintained state, triggered and enabled by a network of intracellular stress responses that can accelerate processes of adaptive evolution. Beyond shedding light on the basis of persistence, these findings raise the possibility that persisters behave as an evolutionary reservoir from which resistant organisms can emerge. As persistence and its consequences come into clearer focus, so too does the need for clinically useful persister-eradication strategies.

Cancer as a metabolic disease: implications for novel therapeutics

Emerging evidence indicates that cancer is primarily a metabolic disease involving disturbances in energy production through respiration and fermentation. The genomic instability observed in tumor cells and all other recognized hallmarks of cancer are considered downstream epiphenomena of the initial disturbance of cellular energy metabolism. The disturbances in tumor cell energy metabolism can be linked to abnormalities in the structure and function of the mitochondria. When viewed as a mitochondrial metabolic disease, the evolutionary theory of Lamarck can better explain cancer progression than can the evolutionary theory of Darwin. Cancer growth and progression can be managed following a whole body transition from fermentable metabolites, primarily glucose and glutamine, to respiratory metabolites, primarily ketone bodies. As each individual is a unique metabolic entity, personalization of metabolic therapy as a broad-based cancer treatment strategy will require fine-tuning to match the therapy to an individual’s unique physiology.

A new criterion for demarcating life from non-life

Criteria for demarcating life from non-life are important for deciding whether new candidate systems, either discovered extraterrestrially or constructed in the laboratory, are genuinely alive or not. They are also important for understanding the origin of life and its evolution. Current criteria are either too restrictive or too extensive. The new criterion proposed here poses that a system is living when it is capable of utilizing active causation, at evolutionary or behavioural timescales. Active causation is produced when the organism uses an estimate of its own Darwinian fitness to modulate the variance of stochasticity that drives hereditary or behavioural changes. The changes are subsequently fed back to the fitness estimate and used in the next cycle of a feedback loop. The ability to use a self-estimated fitness in this way is an evolved property of the organism, and the way in which fitness is estimated is therefore controlled and stabilized by Darwinian evolution. The hereditary and behavioural trajectories resulting from this mechanism combine predictability with unpredictability, and the mechanism produces a form of self-directed agency in living organisms that is absent from non-living systems.

PortEco: a resource for exploring bacterial biology through high-throughput data and analysis tools

PortEco (http://porteco.org) aims to collect, curate and provide data and analysis tools to support basic biological research in Escherichia coli (and eventually other bacterial systems). PortEco is implemented as a ‘virtual’ model organism database that provides a single unified interface to the user, while integrating information from a variety of sources. The main focus of PortEco is to enable broad use of the growing number of high-throughput experiments available for E. coli, and to leverage community annotation through the EcoliWiki and GONUTS systems. Currently, PortEco includes curated data from hundreds of genome-wide RNA expression studies, from high-throughput phenotyping of single-gene knockouts under hundreds of annotated conditions, from chromatin immunoprecipitation experiments for tens of different DNA-binding factors and from ribosome profiling experiments that yield insights into protein expression. Conditions have been annotated with a consistent vocabulary, and data have been consistently normalized to enable users to find, compare and interpret relevant experiments. PortEco includes tools for data analysis, including clustering, enrichment analysis and exploration via genome browsers. PortEco search and data analysis tools are extensively linked to the curated gene, metabolic pathway and regulation content at its sister site, EcoCyc.

Elevated mutagenesis does not explain the increased frequency of antibiotic resistant mutants in starved aging colonies

The frequency of mutants resistant to the antibiotic rifampicin has been shown to increase in aging (starved), compared to young colonies of Eschierchia coli. These increases in resistance frequency occur in the absence of any antibiotic exposure, and similar increases have also been observed in response to additional growth limiting conditions. Understanding the causes of such increases in the frequency of resistance is important for understanding the dynamics of antibiotic resistance emergence and spread. Increased frequency of rifampicin resistant mutants in aging colonies is cited widely as evidence of stress-induced mutagenesis (SIM), a mechanism thought to allow bacteria to increase mutation rates upon exposure to growth-limiting stresses. At the same time it has been demonstrated that some rifampicin resistant mutants are relatively fitter in aging compared to young colonies, indicating that natural selection may also contribute to increased frequency of rifampicin resistance in aging colonies. Here, we demonstrate that the frequency of mutants resistant to both rifampicin and an additional antibiotic (nalidixic-acid) significantly increases in aging compared to young colonies of a lab strain of Escherichia coli. We then use whole genome sequencing to demonstrate conclusively that SIM cannot explain the observed magnitude of increased frequency of resistance to these two antibiotics. We further demonstrate that, as was previously shown for rifampicin resistance mutations, mutations conferring nalidixic acid resistance can also increase fitness in aging compared to young colonies. Our results show that increases in the frequency of antibiotic resistant mutants in aging colonies cannot be seen as evidence of SIM. Furthermore, they demonstrate that natural selection likely contributes to increases in the frequency of certain antibiotic resistance mutations, even when no selection is exerted due to the presence of antibiotics.

Antibiotic resistance is one of the most pressing threats on human health worldwide. Such resistance has been increasing largely due to widespread antibiotic usage. However, it has also been noticed that under certain growth limiting conditions, there is an increase in resistance frequency that is independent of the presence of antibiotics. Such increases in antibiotic resistance frequency can greatly affect the dynamics of antibiotic resistance emergence and spread. Yet currently their causes are far from understood. Many assume that we observe more resistance mutations when growth is limited, because more mutations occur under such conditions. Here we use whole genome sequencing to show that increases in resistance frequency to two different antibiotics under starvation cannot be explained by increased mutagenesis. We further show that at least some of the increase in resistance frequency is likely to be explained by natural selection that favors certain resistance mutations conferring increased fitness under starvation. These results are intriguing as they demonstrate that positive selection may contribute to increases in the frequency of certain antibiotic resistance mutations, even in the absence of selection exerted by the presence of antibiotics.

Engineered proteins detect spontaneous DNA breakage in human and bacterial cells

Spontaneous DNA breaks instigate genomic changes that fuel cancer and evolution, yet direct quantification of double-strand breaks (DSBs) has been limited. Predominant sources of spontaneous DSBs remain elusive. We report synthetic technology for quantifying DSBs using fluorescent-protein fusions of double-strand DNA end-binding protein, Gam of bacteriophage Mu. In Escherichia coli GamGFP forms foci at chromosomal DSBs and pinpoints their subgenomic locations. Spontaneous DSBs occur mostly one per cell, and correspond with generations, supporting replicative models for spontaneous breakage, and providing the first true breakage rates. In mammalian cells GamGFP-labels laser-induced DSBs antagonized by end-binding protein Ku; co-localizes incompletely with DSB marker 53BP1 suggesting superior DSB-specificity; blocks resection; and demonstrates DNA breakage via APOBEC3A cytosine deaminase. We demonstrate directly that some spontaneous DSBs occur outside of S phase. The data illuminate spontaneous DNA breakage in E. coli and human cells and illustrate the versatility of fluorescent-Gam for interrogation of DSBs in living cells. DOI:http://dx.doi.org/10.7554/eLife.01222.001.

Hypermutability and error catastrophe due to defects in ribonucleotide reductase

The enzyme ribonucleotide reductase (RNR) plays a critical role in the production of deoxynucleoside-5'-triphosphates (dNTPs), the building blocks for DNA synthesis and replication. The levels of the cellular dNTPs are tightly controlled, in large part through allosteric control of RNR. One important reason for controlling the dNTPs relates to their ability to affect the fidelity of DNA replication and, hence, the cellular mutation rate. We have previously isolated a set of mutants of Escherichia coli RNR that are characterized by altered dNTP pools and increased mutation rates (mutator mutants). Here, we show that one particular set of RNR mutants, carrying alterations at the enzyme's allosteric specificity site, is characterized by relatively modest dNTP pool deviations but exceptionally strong mutator phenotypes, when measured in a mutational forward assay (>1,000-fold increases). We provide evidence indicating that this high mutability is due to a saturation of the DNA mismatch repair system, leading to hypermutability and error catastrophe. The results indicate that, surprisingly, even modest deviations of the cellular dNTP pools, particularly when the pool deviations promote particular types of replication errors, can have dramatic consequences for mutation rates.

In Darwinian evolution, feedback from natural selection leads to biased mutations

Natural selection provides feedback through which information about the environment and its recurring challenges is captured, inherited, and accumulated within genomes in the form of variations that contribute to survival. The variation upon which natural selection acts is generally described as "random." Yet evidence has been mounting for decades, from such phenomena as mutation hotspots, horizontal gene transfer, and highly mutable repetitive sequences, that variation is far from the simplifying idealization of random processes as white (uniform in space and time and independent of the environment or context).  This paper focuses on what is known about the generation and control of mutational variation, emphasizing that it is not uniform across the genome or in time, not unstructured with respect to survival, and is neither memoryless nor independent of the (also far from white) environment. We suggest that, as opposed to frequentist methods, Bayesian analysis could capture the evolution of nonuniform probabilities of distinct classes of mutation, and argue not only that the locations, styles, and timing of real mutations are not correctly modeled as generated by a white noise random process, but that such a process would be inconsistent with evolutionary theory.

Structural insight into LexA-RecA* interaction

RecA protein is a hallmark for the bacterial response to insults inflicted on DNA. It catalyzes the strand exchange step of homologous recombination and stimulates self-inactivation of the LexA transcriptional repressor. Importantly, by these activities, RecA contributes to the antibiotic resistance of bacteria. An original way to decrease the acquisition of antibiotic resistance would be to block RecA association with LexA. To engineer inhibitors of LexA–RecA complex formation, we have mapped the interaction area between LexA and active RecA–ssDNA filament (RecA*) and generated a three-dimensional model of the complex. The model revealed that one subunit of the LexA dimer wedges into a deep helical groove of RecA*, forming multiple interaction sites along seven consecutive RecA protomers. Based on the model, we predicted that LexA in its DNA-binding conformation also forms a complex with RecA* and that the operator DNA sterically precludes interaction with RecA*, which guides the induction of SOS gene expression. Moreover, the model shows that besides the catalytic C-terminal domain of LexA, its N-terminal DNA-binding domain also interacts with RecA*. Because all the model-based predictions have been confirmed experimentally, the presented model offers a validated insight into the critical step of the bacterial DNA damage response.

Selection-driven accumulation of suppressor mutants in bacillus subtilis: the apparent high mutation frequency of the cryptic gudB gene and the rapid clonal expansion of gudB(+) suppressors are due to growth under selection

Soil bacteria like Bacillus subtilis can cope with many growth conditions by adjusting gene expression and metabolic pathways. Alternatively, bacteria can spontaneously accumulate beneficial mutations or shape their genomes in response to stress. Recently, it has been observed that a B. subtilis mutant lacking the catabolically active glutamate dehydrogenase (GDH), RocG, mutates the cryptic gudB^CR gene at a high frequency. The suppressor mutants express the active GDH GudB, which can fully replace the function of RocG. Interestingly, the cryptic gudB^CR allele is stably inherited as long as the bacteria synthesize the functional GDH RocG. Competition experiments revealed that the presence of the cryptic gudB^CR allele provides the bacteria with a selective growth advantage when glutamate is scarce. Moreover, the lack of exogenous glutamate is the driving force for the selection of mutants that have inactivated the active gudB gene. In contrast, two functional GDHs are beneficial for the cells when glutamate was available. Thus, the amount of GDH activity strongly affects fitness of the bacteria depending on the availability of exogenous glutamate. At a first glance the high mutation frequency of the cryptic gudB^CR allele might be attributed to stress-induced adaptive mutagenesis. However, other loci on the chromosome that could be potentially mutated during growth under the selective pressure that is exerted on a GDH-deficient mutant remained unaffected. Moreover, we show that a GDH-proficient B. subtilis strain has a strong selective growth advantage in a glutamate-dependent manner. Thus, the emergence and rapid clonal expansion of the active gudB allele can be in fact explained by spontaneous mutation and growth under selection without an increase of the mutation rate. Moreover, this study shows that the selective pressure that is exerted on a maladapted bacterium strongly affects the apparent mutation frequency of mutational hot spots.

R-loops and nicks initiate DNA breakage and genome instability in non-growing Escherichia coli

Double-stranded DNA ends, often from replication, drive genomic instability, yet their origin in non-replicating cells is unknown. Here we show that transcriptional RNA/DNA hybrids (R-loops) generate DNA ends that underlie stress-induced mutation and amplification. Depleting RNA/DNA hybrids with overproduced RNase HI reduces both genomic changes, indicating RNA/DNA hybrids as intermediates in both. An Mfd requirement and inhibition by translation implicate transcriptional R-loops. R-loops promote instability by generating DNA ends, shown by their dispensability when ends are provided by I-SceI endonuclease. Both R-loops and single-stranded endonuclease TraI are required for end formation, visualized as foci of a fluorescent end-binding protein. The data suggest that R-loops prime replication forks that collapse at single-stranded nicks, producing ends that instigate genomic instability. The results illuminate how DNA ends form in non-replicating cells, identify R-loops as the earliest known mutation/amplification intermediate, and suggest that genomic instability during stress could be targeted to transcribed regions, accelerating adaptation.