Enhancing transcription in Escherichia coli and Pseudomonas putida using bacteriophage lambda anti-terminator protein Q

Functional characterization of metagenomic DNA often involves expressing heterologous DNA in genetically tractable microorganisms such as Escherichia coli. Functional expression of heterologous genes can suffer from limitations due to the lack of recognition of foreign promoters or presence of intrinsic terminators on foreign DNA between a vector-based promoter and the transcription start site. Anti-terminator proteins are a possible solution to overcome this limitation. When bacteriophage lambda infects E. coli, it relies on the host transcription machinery to transcribe and express phage DNA. Lambda anti-terminator protein Q (λQ) regulates the expression of late-genes of phage lambda. E. coli RNA polymerase recognizes the P_R' promoter on the lambda genome and forms a complex with λQ, to overcome the terminator t_R'. Here we show the use of λQ to efficiently transcribe a capsular polysaccharide cluster, cps3, from Lactobacillus plantarum containing intrinsic terminators in Escherichia coli. In addition, we expand the use of anti-terminator λQ in Pseudomonas putida. The results show ~ fivefold higher expression of a fluorescent reporter located ~ 12.5kbp downstream from the promoter, when the transcription is driven by P_R' promoter in presence of λQ compared to a lac promoter. These results suggest that λQ could be used in metabolic engineering to enhance expression of heterologous DNA.

Adaptive laboratory evolution of β-caryophyllene producing Saccharomyces cerevisiae

Background

β-Caryophyllene is a plant terpenoid with therapeutic and biofuel properties. Production of terpenoids through microbial cells is a potentially sustainable alternative for production. Adaptive laboratory evolution is a complementary technique to metabolic engineering for strain improvement, if the product-of-interest is coupled with growth. Here we use a combination of pathway engineering and adaptive laboratory evolution to improve the production of β-caryophyllene, an extracellular product, by leveraging the antioxidant potential of the compound.

Results

Using oxidative stress as selective pressure, we developed an adaptive laboratory evolution that worked to evolve an engineered β-caryophyllene producing yeast strain for improved production within a few generations. This strategy resulted in fourfold increase in production in isolated mutants. Further increasing the flux to β-caryophyllene in the best evolved mutant achieved a titer of 104.7 ± 6.2 mg/L product. Genomic analysis revealed a gain-of-function mutation in the a-factor exporter STE6 was identified to be involved in significantly increased production, likely as a result of increased product export.

Conclusion

An optimized selection strategy based on oxidative stress was developed to improve the production of the extracellular product β-caryophyllene in an engineered yeast strain. Application of the selection strategy in adaptive laboratory evolution resulted in mutants with significantly increased production and identification of novel responsible mutations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01598-z.

Beneficial mutations for carotenoid production identified from laboratory-evolved Saccharomyces cerevisiae

Adaptive laboratory evolution (ALE) is a powerful tool used to increase strain fitness in the presence of environmental stressors. If production and strain fitness can be coupled, ALE can be used to increase product formation. In earlier work, carotenoids hyperproducing mutants were obtained using an ALE strategy. Here, de novo mutations were identified in hyperproducers, and reconstructed mutants were explored to determine the exact impact of each mutation on production and tolerance. A single mutation in YMRCTy1-3 conferred increased carotenoid production, and when combined with other beneficial mutations led to further increased β-carotene production. Findings also suggest that the ALE strategy selected for mutations that confer increased carotenoid production as primary phenotype. Raman spectroscopy analysis and total lipid quantification revealed positive correlation between increased lipid content and increased β-carotene production. Finally, we demonstrated that the best combinations of mutations identified for β-carotene production were also beneficial for production of lycopene.

Identifying novel genetic determinants for oxidative stress tolerance in Candida glabrata via adaptive laboratory evolution

Candida glabrata (C glabrata) is an important yeast of industrial and medical significance. Resistance to oxidative stress is an important trait affecting its robustness as a production host or virulence as a pathogenic agent, but current understanding of resistance mechanisms is still limited in this fungus. In this study, we rapidly evolved C glabrata population to adapt to oxidative challenge (from 80mM to 350mM of H₂ O₂ ) through short-term adaptive laboratory evolution. Adaptive mutants were isolated from evolved populations and subjected to phenotypic and omics analyses to identify potential mechanisms of tolerance to H₂ O₂ . Phenotypic characterizations revealed faster detoxification of H₂ O₂ and ability to initiate growth at a higher concentration of the oxidant in the isolated adaptive mutants compared with the wild type. Genome resequencing and genome-wide transcriptome analysis revealed multiple genetic determinants (eg, CAGL0E01243g, CAGL0F06831g, and CAGL0C00385g) that potentially contribute to enhanced H₂ O₂ resistance. Subsequent experimental verification confirmed that CgCth2 (CAGL0E01243g) and CgMga2 (CAGL0F06831g) are important in C glabrata tolerance to oxidative stress. Transcriptome profiling of adaptive mutants and bioinformatic analysis suggest that NADPH regeneration, modulation of membrane composition, cell wall remodeling, and/or global regulatory changes are involved in C glabrata tolerance to H₂ O₂ .

Insights on Osmotic Tolerance Mechanisms in Escherichia coli Gained from an rpoC Mutation

An 84 bp in-frame duplication (K370_A396dup) within the rpoC subunit of RNA polymerase was found in two independent mutants selected during an adaptive laboratory evolution experiment under osmotic stress in Escherichia coli, suggesting that this mutation confers improved osmotic tolerance. To determine the role this mutation in rpoC plays in osmotic tolerance, we reconstructed the mutation in BW25113, and found it to confer improved tolerance to hyperosmotic stress. Metabolite analysis, exogenous supplementation assays, and cell membrane damage analysis suggest that the mechanism of improved osmotic tolerance by this rpoC mutation may be related to the higher production of acetic acid and amino acids such as proline, and increased membrane integrity in the presence of NaCl stress in exponential phase cells. Transcriptional analysis led to the findings that the overexpression of methionine related genes metK and mmuP improves osmotic tolerance in BW25113. Furthermore, deletion of a stress related gene bolA was found to confer enhanced osmotic tolerance in BW25113 and MG1655. These findings expand our current understanding of osmotic tolerance in E. coli, and have the potential to expand the utilization of high saline feedstocks and water sources in microbial fermentation.

Characterization of an evolved carotenoids hyper-producer of Saccharomyces cerevisiae through bioreactor parameter optimization and Raman spectroscopy

An evolutionary engineering approach for enhancing heterologous carotenoids production in an engineered Saccharomyces cerevisiae strain was used previously to isolate several carotenoids hyper-producers from the evolved populations. β-Carotene production was characterized in the parental and one of the evolved carotenoids hyper-producers (SM14) using bench-top bioreactors to assess the impact of pH, aeration, and media composition on β-carotene production levels. The results show that with maintaining a low pH and increasing the carbon-to-nitrogen ratio (C:N) from 8.8 to 50 in standard YNB medium, a higher β-carotene production level at 25.52 ± 2.15 mg β-carotene g−1 (dry cell weight) in the carotenoids hyper-producer was obtained. The increase in C:N ratio also significantly increased carotenoids production in the parental strain by 298 % [from 5.68 ± 1.24 to 22.58 ± 0.11 mg β-carotene g−1 (dcw)]. In this study, it was shown that Raman spectroscopy is capable of monitoring β-carotene production in these cultures. Raman spectroscopy is adaptable to large-scale fermentations and can give results in near real-time. Furthermore, we found that Raman spectroscopy was also able to measure the relative lipid compositions and protein content of the parental and SM14 strains at two different C:N ratios in the bioreactor. The Raman analysis showed a higher total fatty acid content in the SM14 compared with the parental strain and that an increased C:N ratio resulted in significant increase in total fatty acid content of both strains. The data suggest a positive correlation between the yield of β-carotene per biomass and total fatty acid content of the cell.

Recent progress in biobutanol tolerance in microbial systems with an emphasis on Clostridium

Biobased production of butanol promises a more sustainable route for industrial production. However, butanol toxicity remains a barrier for achieving high product titers. Investigation into butanol stress has shed some light on its modes of toxicity. Unfortunately, there still remain significant shortfalls in our understanding of the complex interactions of butanol with cells. To address this knowledge gap, a diverse range of tools have been employed to gain a better understanding of the adverse effects of butanol on the cell. These findings have lead to the identification of possible molecular mechanisms associated with butanol tolerance, which can be harnessed for future strain development efforts. This review focuses on recent efforts to address the toxicity of butanol in microbial producers and offers some perspectives on the future direction of this research sector.

Stevens-Johnson syndrome and toxic epidermal necrolysis in patients with malignancies

BACKGROUND

Malignancy is known to be associated with an increased mortality rate in patients with Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). However, risk factors contributing to the poor prognosis of patients with SJS/TEN with malignancies remain undefined.

OBJECTIVES

To explore the potential involvement of malignancy and its related factors contributing to the poor outcome of SJS/TEN, in a retrospective study.

METHODS

In total 517 patients with SJS/TEN were enrolled. Forty-seven who sustained various types of malignancies were analysed for numerous malignancy-related factors, including cancer types, clinical stages and chemotherapies given or not before the onset of SJS/TEN.

RESULTS

We found that the mortality rate of patients with SJS/TEN with malignancies was higher than that of patients without malignancies (32%, 15/47 vs. 8·5%, 40/470, respectively) (P < 0·001). The use of phenytoin was significantly higher in the malignancy group. The presence of hepatocellular carcinoma (80%, four of five; P < 0·001; odds ratio 43) and colorectal cancer (67%, two of three; P = 0·022; odds ratio 21·5) significantly increased the death rate of patients with SJS/TEN, whereas lung cancer and urothelial carcinoma did not. Patients who had received ongoing or recent chemotherapy showed higher mortality than those without chemotherapy (P = 0·022; odds ratio 4·95). Furthermore, among the 47 patients with SJS/TEN with malignancies, lower serum albumin, haemoglobin and platelet count were detected in the deceased patients than in the surviving patients before the onset of SJS/TEN.

CONCLUSIONS

Our results suggest that several factors related to malignancies, such as specific cancer types, chemotherapy and malnutrition, may contribute to poor prognosis in patients with malignancies developing SJS/TEN.

Genome shuffling to generate recombinant yeasts for tolerance to inhibitors present in lignocellulosic hydrolysates

OBJECTIVES

To investigate the use of genome shuffling to generate recombinants from previously generated hydrolysates-tolerant strains to improve tolerance of Saccharomyces cerevisiae to one or more inhibitory by-products present in lignocellulosic hydrolysates.

RESULTS

Recombinants of previously evolved strains of S. cerevisiae were generated and analyzed for their relative performance in the individual inhibitors furfural, acetic acid, 5-(hydroxymethyl)-furfural (HMF) and in synthetic hydrolysates. One recombinant exhibited a 100 % fitness increase in the presence of HMF as compared to the wild-type diploid, while another stain exhibited a 13 % fitness increase in the presence of furfural. Furthermore, for one of these recombinants, these increases in fitness were specific to the inhibitor HMF and to synthetic hydrolysates rather than being due to a general increase in fitness. Mutations present in the evolved hydrolysates-tolerant mutants were identified via whole-genome resequencing.

CONCLUSION

Recombinants of S. cerevisiae were produced with increased tolerance to inhibitory by-products present in hydrolysates of lignocellulosic biomass and identified potential genetic determinants associated with this phenotype.

Improving carotenoids production in yeast via adaptive laboratory evolution

Adaptive laboratory evolution is an important tool for the engineering of strains for industrially relevant phenotypes. Traditionally, adaptive laboratory evolution has been implemented to improve robustness of industrial strains under diverse operational conditions; however due to the required coupling between growth and survival, its application for increased production of secondary metabolites generally results in decreased production due to the metabolic burden imposed by, or toxicity of, the produced compound. In this study, adaptive laboratory evolution was successfully applied to improve carotenoids production in an engineered Saccharomyces cerevisiae producer strain by exploiting the antioxidant properties of carotenoids. Short-term evolution experiment using periodic hydrogen peroxide shocking schemes resulted in a 3-fold increase in carotenoids production (from 6 mg/g dry cell weight to up to 18 mg/g dry cell weight). Subsequent transcriptome analysis was used to elucidate the molecular mechanisms for increased carotenoids production. Upregulation of genes related with lipid biosynthesis and mevalonate biosynthesis pathways were commonly observed in the carotenoids hyper-producers analyzed.

Adaptive laboratory evolution for strain engineering

Complex phenotypes, such as tolerance to growth inhibitors, are difficult to rationally engineer into industrial model organisms due our poor understanding of their underlying molecular mechanisms. Adaptive evolution circumvents this issue by exploiting the linkage between growth rate and inhibitor resistance to select for mutants with enhanced tolerance. In order to aid experimentalists in the design and execution of adaptive laboratory evolution, we present detailed protocols for batch, continuous, and visualizing evolution in real-time (VERT) approaches to this technique.

Visualizing evolution in real-time method for strain engineering

The adaptive landscape for an industrially relevant phenotype is determined by the effects of the genetic determinants on the fitness of the microbial system. Identifying the underlying adaptive landscape for a particular phenotype of interest will greatly enhance our abilities to engineer more robust microbial strains. Visualizing evolution in real-time (VERT) is a recently developed method based on in vitro adaptive evolution that facilitates the identification of fitter mutants throughout the course of evolution. Combined with high-throughput genomic tools, VERT can greatly enhance the mapping of adaptive landscapes of industrially relevant phenotypes in microbial systems, thereby expanding our knowledge on the parameters that can be used for strain engineering.

Visualizing evolution in real time to determine the molecular mechanisms of n-butanol tolerance in Escherichia coli

Toxicity of products or feedstock components poses a challenge in the biocatalyst-based production of fuels and chemicals. The genetic determinants that are involved in increased resistance to an inhibitor form the adaptive landscape for the phenotype; so in order to engineer more robust biocatalysts, a better understanding of the adaptive landscape is required. Here, we used an adaptive laboratory evolution method called visualizing evolution in real time (VERT) to help map out part of the adaptive landscape of Escherichia coli tolerance to the biofuel n-butanol. VERT enables identification of adaptive events (population expansions triggered by adaptive mutants) via visualization of the relative proportions of different fluorescently-labeled cells. Knowledge of the occurrence of adaptive events allows for a more systematic isolation of adaptive mutants while simultaneously reducing the number of missed adaptive mutants (and the underlying adaptive mechanisms) that result from clonal interference during the course of in vitro evolution. Based on the evolutionary dynamics observed, clonal interference was found to play a significant role in shaping the population structure of E. coli during exposure to n-butanol, and VERT helped to facilitate the isolation of adaptive mutants from the population. We further combined adaptive laboratory evolution with genome shuffling to significantly enhance the desired n-butanol tolerance phenotype. Subsequent transcriptome analysis of the isolated adaptive mutants revealed different mechanisms of n-butanol resistance in different lineages. In one fluorescently-marked subpopulation, members of the Fur regulon were upregulated; which was not observed in the other subpopulation. In addition, genome sequencing of several adaptive mutants revealed the genetic basis for some of the observed transcriptome profiles. We further elucidated the potential role of the iron-related gene in n-butanol tolerance via overexpression and deletion studies and hypothesized that the upregulation of the iron-related genes indirectly led to modifications in the outer membrane, which contributed to enhanced n-butanol tolerance.

Population dynamics and the evolution of antifungal drug resistance in Candida albicans

Candida albicans is an important human fungal pathogen. Resistance to all major antifungal agents has been observed in clinical isolates of Candida spp. and is a major clinical challenge. The rise and expansion of drug-resistant mutants during exposure to antifungal agents occurs through a process of adaptive evolution, with potentially complex population dynamics. Understanding the population dynamics during the emergence of drug resistance is important for determining the fundamental principles of how fungal pathogens evolve for resistance. While few detailed reports that focus on the population dynamics of C. albicans currently exist, several important features on the population structure and adaptive landscape can be elucidated from existing evolutionary studies in in vivo and in vitro systems.

Transcriptional analysis of Lactobacillus brevis to N-butanol and ferulic acid stress responses

Background

The presence of anti-microbial phenolic compounds, such as the model compound ferulic acid, in biomass hydrolysates pose significant challenges to the widespread use of biomass in conjunction with whole cell biocatalysis or fermentation. Currently, these inhibitory compounds must be removed through additional downstream processing or sufficiently diluted to create environments suitable for most industrially important microbial strains. Simultaneously, product toxicity must also be overcome to allow for efficient production of next generation biofuels such as n-butanol, isopropanol, and others from these low cost feedstocks.

Methodology and Principal Findings

This study explores the high ferulic acid and n-butanol tolerance in Lactobacillus brevis, a lactic acid bacterium often found in fermentation processes, by global transcriptional response analysis. The transcriptional profile of L. brevis reveals that the presence of ferulic acid triggers the expression of currently uncharacterized membrane proteins, possibly in an effort to counteract ferulic acid induced changes in membrane fluidity and ion leakage. In contrast to the ferulic acid stress response, n-butanol challenges to growing cultures primarily induce genes within the fatty acid synthesis pathway and reduced the proportion of 19∶1 cyclopropane fatty acid within the L. brevis membrane. Both inhibitors also triggered generalized stress responses. Separate attempts to alter flux through the Escherichia coli fatty acid synthesis by overexpressing acetyl-CoA carboxylase subunits and deleting cyclopropane fatty acid synthase (cfa) both failed to improve n-butanol tolerance in E. coli, indicating that additional components of the stress response are required to confer n-butanol resistance.

Conclusions

Several promising routes for understanding both ferulic acid and n-butanol tolerance have been identified from L. brevis gene expression data. These insights may be used to guide further engineering of model industrial organisms to better tolerate both classes of inhibitors to enable facile production of biofuels from lignocellulosic biomass.

Genomic library screens for genes involved in n-butanol tolerance in Escherichia coli

Background

n-Butanol is a promising emerging biofuel, and recent metabolic engineering efforts have demonstrated the use of several microbial hosts for its production. However, most organisms have very low tolerance to n-butanol (up to 2% (v/v)), limiting the economic viability of this biofuel. The rational engineering of more robust n-butanol production hosts relies upon understanding the mechanisms involved in tolerance. However, the existing knowledge of genes involved in n-butanol tolerance is limited. The goal of this study is therefore to identify E. coli genes that are involved in n-butanol tolerance.

Methodology/Principal Findings

Using a genomic library enrichment strategy, we identified approximately 270 genes that were enriched or depleted in n-butanol challenge. The effects of these candidate genes on n-butanol tolerance were experimentally determined using overexpression or deletion libraries. Among the 55 enriched genes tested, 11 were experimentally shown to confer enhanced tolerance to n-butanol when overexpressed compared to the wild-type. Among the 84 depleted genes tested, three conferred increased n-butanol resistance when deleted. The overexpressed genes that conferred the largest increase in n-butanol tolerance were related to iron transport and metabolism, entC and feoA, which increased the n-butanol tolerance by 32.8±4.0% and 49.1±3.3%, respectively. The deleted gene that resulted in the largest increase in resistance to n-butanol was astE, which enhanced n-butanol tolerance by 48.7±6.3%.

Conclusions/Significance

We identified and experimentally verified 14 genes that decreased the inhibitory effect of n-butanol tolerance on E. coli. From the data, we were able to expand the current knowledge on the genes involved in n-butanol tolerance; the results suggest that an increased iron transport and metabolism and decreased acid resistance may enhance n-butanol tolerance. The genes and mechanisms identified in this study will be helpful in the rational engineering of more robust biofuel producers.

A genome-wide analysis reveals no nuclear dobzhansky-muller pairs of determinants of speciation between S. cerevisiae and S. paradoxus, but suggests more complex incompatibilities

The Dobzhansky-Muller (D-M) model of speciation by genic incompatibility is widely accepted as the primary cause of interspecific postzygotic isolation. Since the introduction of this model, there have been theoretical and experimental data supporting the existence of such incompatibilities. However, speciation genes have been largely elusive, with only a handful of candidate genes identified in a few organisms. The Saccharomyces sensu stricto yeasts, which have small genomes and can mate interspecifically to produce sterile hybrids, are thus an ideal model for studying postzygotic isolation. Among them, only a single D-M pair, comprising a mitochondrially targeted product of a nuclear gene and a mitochondrially encoded locus, has been found. Thus far, no D-M pair of nuclear genes has been identified between any sensu stricto yeasts. We report here the first detailed genome-wide analysis of rare meiotic products from an otherwise sterile hybrid and show that no classic D-M pairs of speciation genes exist between the nuclear genomes of the closely related yeasts S. cerevisiae and S. paradoxus. Instead, our analyses suggest that more complex interactions, likely involving multiple loci having weak effects, may be responsible for their post-zygotic separation. The lack of a nuclear encoded classic D-M pair between these two yeasts, yet the existence of multiple loci that may each exert a small effect through complex interactions suggests that initial speciation events might not always be mediated by D-M pairs. An alternative explanation may be that the accumulation of polymorphisms leads to gamete inviability due to the activities of anti-recombination mechanisms and/or incompatibilities between the species' transcriptional and metabolic networks, with no single pair at least initially being responsible for the incompatibility. After such a speciation event, it is possible that one or more D-M pairs might subsequently arise following isolation.

Species are defined such that organisms of the same species can produce fertile offspring, whereas organisms of different species are either unable to mate, or when they do, they produce inviable or sterile progeny. A well-known pair of species that can mate yet produce sterile offspring is the horse and donkey, which produce an infertile hybrid, the mule. A long-standing idea for the species barrier is that when certain pairs of genes from the two different species are combined, the genes can no longer function properly, thus causing death or sterility. Identification of these incompatible genes may allow us to determine how organisms form distinct species, and understand the process of speciation itself. We used two closely related yeasts to look for these incompatible genes by isolating rare viable hybrid offspring, and looking for excluded gene combinations. We did not find any pairs of incompatible genes, but instead found that there appear to be more than two genes involved in such incompatibilities. We speculate that the accumulation of large numbers of sequence differences in their DNA may cause defects in how genes are controlled in hybrids, causing these two yeasts to be independent species.

Molecular characterization of clonal interference during adaptive evolution in asexual populations of Saccharomyces cerevisiae

The classical model of adaptive evolution in an asexual population postulates that each adaptive clone is derived from the one preceding it1. However, experimental evidence suggests more complex dynamics2-5 with theory predicting the fixation probability of a beneficial mutation as dependent on the mutation rate, population size, and the mutation's selection coefficient6. Clonal interference has been demonstrated in viruses7 and bacteria8, but has not been demonstrated in a eukaryote and a detailed molecular characterization is lacking. Here we use different fluorescent markers to visualize the dynamics of asexually evolving yeast populations. For each adaptive clone within one of our evolving populations, we have identified the underlying mutations, monitored their population frequencies and used microarrays to characterize changes in the transcriptome. These data provide the most detailed molecular characterization of an experimental evolution to date, and provide direct experimental evidence supporting both the clonal interference and the multiple mutation models.

A global regulatory role of gluconeogenic genes in Escherichia coli revealed by transcriptome network analysis

In bacterial adaptation to the dynamic environment, metabolic genes are typically thought to be the executors, whereas global transcription regulators are regarded as the decision makers. Although the feedback from metabolic consequence is believed to be important, much less is understood. This work demonstrates that the gluconeogenic genes in Escherichia coli, ppsA, sfcA, and maeB, provide a feedback loop to the global regulator, cAMP receptor protein (CRP), in carbon source transition. Disruption of one of the gluconeogenic pathways has no phenotype in balanced growth, but causes a significant delay in the diauxic transition from glucose to acetate. To investigate the underlying mechanism, we measured the transcriptome profiles during the transition using DNA microarray, and network component analysis was employed to obtain the transcription factor activities. Results showed that one of the global regulators, CRP, was insufficiently activated during the transition in the ppsA deletion mutant. Indeed, addition of cAMP partially rescued the delay in transition. These results suggest that the gluconeogenic flux to phosphoenolpyruvate is important for full activation of adenylate cyclase through the phosphorylated enzyme IIA(glu) of the phosphotransferase system. Reduction of this flux causes insufficient activation of CRP and a global metabolic deficiency, which exemplifies a significant feedback interaction from metabolism to the a global regulatory system.

gNCA: a framework for determining transcription factor activity based on transcriptome: identifiability and numerical implementation

Network Component Analysis (NCA) is a network structure-driven framework for deducing regulatory signal dynamics. In contrast to classical approaches such as principal component analysis or independent component analysis, NCA makes use of the connectivity structure from transcriptional regulatory networks to restrict the decomposition to a unique solution. However, the existing version of NCA cannot incorporate information beyond the network topology such as information obtained from regulatory gene knockouts that constrain the dynamics of regulatory signals. The ability of incorporating such information enables a more accurate and self-consistent analysis over different experiments and extends NCA to systems that may not satisfy the identifiability criteria of NCA. In this paper, we derive a generalized form of NCA, gNCA, which significantly expands the capability of transcription network analysis by incorporating regulatory signal constraints arising from genetic knockouts. The theoretical bases including criteria for uniqueness of solution and distinguishability between networks are derived. In addition, numerical techniques for robust decomposition are discussed. gNCA is then demonstrated using an Escherichia coli wild-type strain and an isogenic arcA deletion mutant during a carbon source transition.

Transcriptome-based determination of multiple transcription regulator activities in Escherichia coli by using network component analysis

Cells adjust gene expression profiles in response to environmental and physiological changes through a series of signal transduction pathways. Upon activation or deactivation, the terminal regulators bind to or dissociate from DNA, respectively, and modulate transcriptional activities on particular promoters. Traditionally, individual reporter genes have been used to detect the activity of the transcription factors. This approach works well for simple, non-overlapping transcription pathways. For complex transcriptional networks, more sophisticated tools are required to deconvolute the contribution of each regulator. Here, we demonstrate the utility of network component analysis in determining multiple transcription factor activities based on transcriptome profiles and available connectivity information regarding network connectivity. We used Escherichia coli carbon source transition from glucose to acetate as a model system. Key results from this analysis were either consistent with physiology or verified by using independent measurements.

A Software Package for cDNA Microarray Data Normalization and Assessing Confidence Intervals

DNA microarray data are affected by variations from a number of sources. Before these data can be used to infer biological information, the extent of these variations must be assessed. Here we describe an open source software package, lcDNA, that provides tools for filtering, normalizing, and assessing the statistical significance of cDNA microarray data. The program employs a hierarchical Bayesian model and Markov Chain Monte Carlo simulation to estimate gene-specific confidence intervals for each gene in a cDNA microarray data set. This program is designed to perform these primary analytical operations on data from two-channel spotted, or in situ synthesized, DNA microarrays.

Global expression profiling of acetate-grown Escherichia coli

This study characterized the transcript profile of Escherichia coli in acetate cultures using DNA microarray on glass slides. Glucose-grown cultures were used as a reference. At the 95% confidence level, 354 genes were up-regulated in acetate, while 370 genes were down-regulated compared with the glucose-grown culture. Generally, more metabolic genes were up-regulated in acetate than other gene groups, while genes involved in cell replication, transcription, and translation machinery tended to be down-regulated. It appears that E. coli commits more resources to metabolism at the expense of growth when cultured in the poor carbon source. The expression profile confirms many known features in acetate metabolism such as the induction of the glyoxylate pathway, tricarboxylic acid cycle, and gluconeogenic genes. It also provided many previously unknown features, including induction of malic enzymes, ppsA, and the glycolate pathway and repression of glycolytic and glucose phosphotransferase genes in acetate. The carbon flux delivered from the malic enzymes and PpsA in acetate was further confirmed by deletion mutations. In general, the gene expression profiles qualitatively agree with the metabolic flux changes and may serve as a predictor for gene function and metabolic flux distribution.

Hypokalemic muscular paralysis causing acute respiratory failure due to rhabdomyolysis with renal tubular acidosis in a chronic glue sniffer

CASE REPORT

A 34-year-old male was admitted to the emergency department with the development of quadriparesis and respiratory failure due to hypokalemia after prolonged glue sniffing. The patient was subsequently given mechanical ventilatory support for respiratory failure. He was weaned from the ventilator 4 days later after potassium replacement. Toluene is an aromatic hydrocarbon found in glues, cements, and solvents. It is known to be toxic to the nervous system, hematopoietic system, and causes acid-base and electrolyte disorders. Acute respiratory failure with hypokalemia and rhabdomyolysis with acute renal failure should be considered as potential events in a protracted glue sniffing.

Outcomes and APACHE II predictions for critically ill patients with acute renal failure requiring dialysis

BACKGROUND

Despite the widespread availability of dialytic and intensive care unit technology, the probability of early mortality in critically ill patients with acute renal failure (ARF) is still high, and the evaluation of the patients' prognosis has been difficult. The Acute Physiology and Chronic Health Evaluation II (APACHE II) score is a reliable indicator of severity of illness and likelihood of survival in critically ill patients with ARF. We have attempted to determine whether the APACHE II scoring system can be used to predict prognosis.

METHODS

A retrospective cohort study evaluated the medical records of 100 consecutive patients in intensive care units with acute renal failure who required dialysis from January 1997 through December 1998.

RESULTS

Of the 100 patients studied, 65 were men and 35 were women. The mean age of survivors and nonsurvivors was 59.4 +/- 20.3 years and 58.3 +/- 20.0 years. The overall mortality rate was 71%. There were no significant differences between survivors and nonsurvivors in age, gender, or indication for dialysis. The cause of death in the majority of patients was related to higher APACHE II score during the 24 hours immediately preceding the initiation of acute hemodialysis, and carry mortality rates exceeding 85% with an APACHE II score of 24 or higher.

CONCLUSION

We conclude that mortality rate for acute renal failure in intensive care unit patients continues to be high. The use of the APACHE II score determined at the time of initiation of dialysis for patients with ARF is a statistically significant predictor of patient survival. There is a significant trend with APACHE II score for outcome.

Hyperkalemic cardiac arrest successfully reversed by hemodialysis during cardiopulmonary resuscitation: case report

Severe hyperkalemia is a potential life-threatening cardiac emergency especially in the patients who suffer from a defective renal capacity to excrete potassium such as the dialysis patient. Various conventional therapies including intravenous sodium bicarbonate, insulin with glucose and several beta-2 agonists are commonly employed as transient measures to enhance shift of potassium from the extracellular to the intracellular compartment. If the potassium load is massive and situation is critical, emergency hemodialysis may be useful. During cardiopulmonary resuscitation, the external cardiac compression can support adequate blood flow for hemodialysis. We report a case of a 68-year-old woman who developed sudden cardiac arrest secondary to hyperkalemia with renal insufficiency. Despite 100 minutes of cardiopulmonary resuscitation and conventional treatment for hyperkalemia, the cardiac arrest still persisted. Hemodialysis was then initiated during cardiopulmonary resuscitation and the patient restored spontaneous heart beat 20 minutes later. There was no neurologic sequela after her recovery. Hemodialysis should be considered early in the course of cardiopulmonary resuscitation in severe hyperkalemia induced cardiac arrest if conventional therapies were judged to be ineffective.

Microwave plasmas for low-temperature dry sterilization

The use of microwave plasmas for dry sterilization has been investigated. The dry-sterilization process is a process similar to plasma etching. Bacteria and viruses can be killed by chemical reactions which disintegrate their bodies and remove them from the surface to be sterilized. The removal of bacteria or viruses from material surfaces is caused by the reaction of activated oxygen species in the plasma with hydrocarbon bonds of the cell wall of the bacteria or the capsid of the viruses. Preliminary experiments indicate that the low-temperature dry sterilization method is easy to use, requires much less time than other methods for sterilization, and is also non-toxic. It is feasible for use in the field of sterilization in dental and medical clinics.

Determination of 2-D thickness distributions of low absorbing thin films by new laser interferometry

New laser interferometry has been developed for determination of thickness distributions of low absorbing films on transparent substrates. This technique is suitable for films with either a gradual change or a step change in thickness. With this technique we have obtained fringe patterns showing the 2-D thickness distribution of Se films. This technique is simple and nondestructive without involving computations for films with low absorption and substrates transparent to the laser beam.

Laser interferometry for the determination of thickness distributions of low absorbing films and their spatial and thickness resolutions

New laser interferometry has been developed, based on the principle that a 2-D fringe pattern can be produced by interference of spatially coherent light beams. To avoid the effect of reflection from the back surface of the substrate, the Brewster angle of incidence is adopted; to suppress the effect of diffraction, a lens or a lens system is used. This laser interferometry is an efficient nondestructive technique for the determination of thickness distributions or uniformities of low absorbing films on transparent substrates over a large area without involving laborious computations. The limitation of spatial resolution, thickness resolution, and visibility of fringes is fully analyzed.

Determination of spatial distributions of thickness and optical constants of thin films by a new optical technique

A new optical technique for the determination of spatial distributions of the thickness and the optical constants of thin films is proposed. This technique is simple and nondestructive involving mainly an ellipsometer and a coherent light source, and no contact to the thin-film samples is required. A theoretical estimation indicates that this technique may provide a spatial resolution close to the diffraction-limited resolution under certain conditions. Possible applications of this technique are also discussed.

Schlieren images observed in electrically stressed dielectric liquids

The liquid motion normally observed in electrically stressed dielectric liquids is mainly caused by two mechanisms: (a) the Coulombic force due to the interaction of the space charge with the field, and (b) the electromechanical force created by the field resulting from the spatial variation of the dielectric constant due to the variation of temperature from domain to domain and from time to time in the liquid. The direction of such a liquid motion depends on which of these two mechanisms is dominant. The schlieren images sometimes observed in liquids under applied fields show mainly the change of the already existing temperature gradients in the liquids, and this change is due to the liquid motion caused by either mechanisms (a) or (b) or both. It is concluded that the schlieren images are directly governed by the temperature distribution in the liquid and have no direct bearing on the formation and distribution of space charges.

Schlieren method for the determination of electric field distributions in dielectrics

On the principle that the spatial distribution of the refractive index produced by a small applied temperature difference is changed due to an electromechanical force created by the field resulting from the spatial variation of the dielectric constant, the electric field distributions in a dielectric system can be determined using the schlieren method. Some experimental results for benzene and n-hexane between two spherical electrodes obtained with this method show the essential features predicted from the space charge effects. This method can be used to study electric field and space charge distributions under both steady and transient conditions.