An integrated network approach identifies the isobutanol response network of Escherichia coli

Isobutanol has emerged as a potential biofuel due to recent metabolic engineering efforts. Here we used gene expression and transcription network connectivity data, genetic knockouts, and network component analysis (NCA) to map the initial isobutanol response network of Escherichia coli under aerobic conditions. NCA revealed profound perturbations to respiration. Further investigation showed ArcA as an important mediator of this response. Quinone/quinol malfunction was postulated to activate ArcA, Fur, and PhoB in this study. In support of this hypothesis, quinone-linked ArcA and Fur target expressions were significantly less perturbed by isobutanol under fermentative growth whereas quinol-linked PhoB target expressions remained activated, and isobutanol impeded growth on glycerol, which requires quinones, more than on glucose. In addition, ethanol, n-butanol, and isobutanol response networks were compared. n-Butanol and isobutanol responses were qualitatively similar, whereas ethanol had notable induction differences of pspABCDE and ndh, whose gene products manage proton motive force. The network described here could aid design and comprehension of alcohol tolerance, whereas the approach provides a general framework to characterize complex phenomena at the systems level

Inferring yeast cell cycle regulators and interactions using transcription factor activities

BACKGROUND: Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA) and its generalized form (gNCA) provide a robust framework for deducing the transcription factor activities (TFAs) from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. RESULTS: Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1). In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5) and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2) of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. CONCLUSION: By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors

Potentiating antibacterial activity by predictably enhancing endogenous microbial ROS production

The ever-increasing incidence of antibiotic-resistant infections combined with a weak pipeline of new antibiotics has created a global public health crisis1. Accordingly, novel strategies for enhancing our antibiotic arsenal are needed. As antibiotics kill bacteria in part by inducing reactive oxygen species (ROS)2–4, we reasoned that targeting microbial ROS production might potentiate antibiotic activity. Here we show that ROS production can be predictably enhanced in Escherichia coli, increasing the bacteria’s susceptibility to oxidative attack. We developed an ensemble, genome-scale metabolic modeling approach capable of predicting ROS production in E. coli. The metabolic network was systematically perturbed and its flux distribution analyzed to identify targets predicted to increase ROS production. In silico–predicted targets were experimentally validated and shown to confer increased susceptibility to oxidants. Validated targets also increased susceptibility to killing by antibiotics. This work establishes a systems-based method to tune ROS production in bacteria and demonstrates that increased microbial ROS production can potentiate killing by oxidants and antibiotics

Development of Persister-FACSeq: a method to massively parallelize quantification of persister physiology and its heterogeneity

Bacterial persisters are thought to underlie the relapse of chronic infections. Knowledge of persister physiology would illuminate avenues for therapeutic intervention; however, such knowledge has remained elusive because persisters have yet to be segregated from other cell types to sufficient purity. This technical hurdle has stymied progress toward understanding persistence. Here we developed Persister-FACSeq, which is a method that uses fluorescence-activated cell sorting, antibiotic tolerance assays, and next generation sequencing to interrogate persister physiology and its heterogeneity. As a proof-of-concept, we used Persister-FACSeq on a library of reporters to study gene expression distributions in non-growing Escherichia coli, and found that persistence to ofloxacin is inversely correlated with the capacity of non-growing cells to synthesize protein. Since Persister-FACSeq can be applied to study persistence to any antibiotic in any environment for any bacteria that can harbor a fluorescent reporter, we anticipate that it will yield unprecedented knowledge of this detrimental phenotype

Stationary-Phase Persisters to Ofloxacin Sustain DNA Damage and Require Repair Systems Only during Recovery

ABSTRACT Chronic infections are a serious health care problem, and bacterial persisters have been implicated in infection reoc-currence. Progress toward finding antipersister therapies has been slow, in part because of knowledge gaps regarding the physi-ology of these rare phenotypic variants. Evidence shows that growth status is important for survival, as nongrowing cultures can have 100-fold more persisters than growing populations. However, additional factors are clearly important, as persisters remain rare even in nongrowing populations. What features, beyond growth inhibition, allow persisters to survive antibiotic stress while the majority of their kin succumb to it remains an open question. To investigate this, we used stationary phase as a model nongrowing environment to study Escherichia coli persistence to ofloxacin. Given that the prevailing model of persistence attri-butes survival to transient dormancy and antibiotic target inactivity, we anticipated that persisters would suffer less damage than their dying kin. However, using genetic mutants, flow cytometry, fluorescence-activated cell sorting, and persistence assays, we discovered that nongrowing ofloxacin persisters experience antibiotic-induced damage that is indistinguishable from that of nonpersisters. Consistent with this, we found that these persisters required DNA repair for survival and that repair machinery was unnecessary until the posttreatment recovery period (after ofloxacin removal). These findings suggest that persistence to ofloxacin is not engendered solely by reduced antibiotic target corruption, demonstrate that what happens following antibiotic stress can be critical to the persistence phenotype, and support the notion that inhibition of DNA damage repair systems could be an effective strategy to eliminate fluoroquinolone persisters

Quantifying Current Events Identifies a Novel Endurance Regulator

In non-growing microbes, proteome turnover is reduced and identification of newly synthesized, low abundance proteins is challenging. Babin and colleagues recently utilized bioorthogonal noncanonical amino acid tagging (BONCAT) to identify actively synthesized proteins in non-growing Pseudomonas aeruginosa, discovering a regulator whose influences range from biofilm formation to secondary metabolism

Erratum: Inhibition of stationary phase respiration impairs persister formation in E. coli

Bacterial persisters are rare phenotypic variants that temporarily tolerate high antibiotic concentrations. Persisters have been hypothesized to underlie the recalcitrance of biofilm infections, and strategies to eliminate these cells have the potential to improve treatment outcomes for many hospital-treated infections. Here we investigate the role of stationary phase metabolism in generation of type I persisters in Escherichia coli, which are those that are formed by passage through stationary phase. We find that persisters are unlikely to derive from bacteria with low redox activity, and that inhibition of respiration during stationary phase reduces persister levels by up to ∼1,000-fold. Loss of stationary phase respiratory activity prevents digestion of endogenous proteins and RNA, which yields bacteria that are more capable of translation, replication and concomitantly cell death when exposed to antibiotics. These findings establish bacterial respiration as a prime target for reducing the number of persisters formed in nutrient-depleted, non-growing populations

Discovery and dissection of metabolic oscillations in the microaerobic nitric oxide response network of Escherichia coli

The virulence of many pathogens depends upon their ability to cope with immune-generated nitric oxide (NO·). In Escherichia coli, the major NO· detoxification systems are Hmp, an NO· dioxygenase (NOD), and NorV, an NO· reductase (NOR). It is well established that Hmp is the dominant system under aerobic conditions, whereas NorV dominates anaerobic conditions; however, the quantitative contributions of these systems under the physiologically relevant microaerobic regime remain ill defined. Here, we investigated NO· detoxification in environments ranging from 0 to 50 μM O2, and discovered a regime in which E. coli NO· defenses were severely compromised, as well as conditions that exhibited oscillations in the concentration of NO·. Using an integrated computational and experimental approach, E. coli NO· detoxification was found to be extremely impaired at low O2 due to a combination of its inhibitory effects on NorV, Hmp, and translational activities, whereas oscillations were found to result from a kinetic competition for O2 between Hmp and respiratory cytochromes. Because at least 777 different bacterial species contain the genetic requirements of this stress response oscillator, we hypothesize that such oscillatory behavior could be a widespread phenomenon. In support of this hypothesis, Pseudomonas aeruginosa, whose respiratory and NO· response networks differ considerably from those of E. coli, was found to exhibit analogous oscillations in low O2 environments. This work provides insight into how bacterial NO· defenses function under the low O2 conditions that are likely to be encountered within host environments