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VINELAND — City officials on Monday unveiled components of an advertising campaign they hope will help flip public perceptions of Vineland from negative to positive for outsiders and residents.
The slogan is Vineland, New Jersey ... Discover the Difference and it arrives with pledges from local businesses and organizations to tie in their own marketing efforts. Various city advertising efforts, from its general website to those of individual departments, also will synchronize.
Mayor Ruben Bermudez outlined the campaign at a news conference in City Council chambers. The campaign starts with statements of support from council members as well as the local business community.
Im happy because it is marketing and branding the city of Vineland, Bermudez said.
In an accompanying statement, the mayor called the slogan memorable and relevant and said the branding effort would have positive impacts on business development and retention.
Residents can expect to see this week the logo and slogan on a city water tower on North Mill Road, a location visible to Route 55 traffic. A city trolley also will be decked out.
In addition, print ads are due out on Wednesday for the second anniversary of Landis Marketplace.
Bermudez is in his fifth month as mayor and development of the campaign started not long after moving into City Halls sixth floor. The Vineland firm Tofanelli & Associates, which was brought in by the administration to do general public relations, developed the campaign.
A better image for the city was a part of Bermudez candidate platform last year. Since taking office, he has talked continuously to groups and residents of his intent to quickly implement an upbeat marketing campaign for New Jerseys largest municipality.
City Council Vice President Paul Spinelli and Councilwoman Angela Calakos joined the mayor for the announcement along with city Economic Development Director Sandy Forosisky.
I love the idea of this new logo, Discover the Difference, Calakos said. Its so exciting to be at the forefront of positive change. And I think that is what this administration is doing.
Spinelli said the city means to reach out to all parts of the business community.
Downtown is an engine, he said. We understand that and we try to move that. But we have so many things that people dont really know about and unfortunately, I think, in the past it was all over the place. And what were trying to do is consolidate it, make it one big message so that people understand what we have to offer them and to sell them.
Representatives of the Greater Vineland Chamber of Commerce, the Vineland Downtown Development District and the Landis MarketPlace also offered endorsements. All have marketing campaigns that will continue under the citys advertising umbrella.
The chamber of commerces campaign is Come Grow With Us. Its Image Committee had solicited ideas for the citys new campaign.
Were excited as a business community to get the businesses in Vineland behind this, unified in one direction, and promote the city as well as attract economic development and build community pride within the city with existing citizens, said Dawn Hunter, executive director of the chamber.
Forosisky, who also chairs the chambers Image Committee, said the slogan is flexible enough to be modified for different target audiences.
Todd Noon, executive director of the VDID, welcomed a unified message.
For a lot of years, the downtown area has sort of been a voice in the wilderness, Noon said. Weve always been treated differently than the city. Thats not a bad thing. The city recognized were a valuable piece of Vineland so were glad to carry that charge with us.
But without the unified message between the downtown and the city and its various departments, you can get a mixed message out there and it doesnt really help to attract businesses, to attract people to raise their families here, to work here, he added.
I think its great that we have a tool that we can use to help collaborate together, whether its a business and downtown or the downtown or the rest of Vineland, said Gary Halloway, manager of Landis MarketPlace.
Michael Tofanelli said that, at least initially, the rebranding will not have a cost because it relies on adapting existing, budgeted marketing efforts.
Tofanelli said the final logo and slogan emerged from a field of about 30 ideas. They were not field tested with polls of consumers, he said.


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'I'm excited about this training camp,' cornerback Nevin Lawson said.
- Filed Under
By any measure, the Lions got huge contributions from their rookie class last year.
First-round pick Ziggy Ansah led the team in sacks, third-rounder Larry Warford played at a Pro Bowl level at right guard, fifth-rounder Sam Martin finished among the league leaders in net punting, and two undrafted rookies, LaAdrian Waddle and Joe Fauria, carved out roles that should only expand going forward.
For the Lions to improve on back-to-back losing seasons and make the playoffs this fall for just the second time since the turn of the millennium, they might need similar contributions from a rookie ...

subset: commoncrawl


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December 1, 2015
September 5, 2012
This morning at approximately 1:45 AM, Officers with the Enterprise Police Department responded to a residence on Grimes Street in reference to a burglary in progress. When they arrived, they discovered that the occupants of the home had been awakened when an unknown subject had forced his way into the residence through the back door. The subject had been subdued by the resident and was being held on the floor when officers arrived. OB Teague 42, of 101 Cinema Drive in Enterprise, was arrested and charged with burglary in the first degree as a result of the incident.
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Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA) and minimization of metabolic adjustment (MOMA) were used as modeling frameworks.
The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed.
The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.
Lactic acid bacteria (LAB) are a heterogeneous group of microorganisms able to convert carbohydrates into lactic acid. They are applied worldwide in the industrial manufacture of fermented food products, mainly in the dairy industry. During fermentation LAB primarily produce lactic acid from the available carbon source, resulting in the rapid acidification of the food raw material, which is an important parameter in the preservation and extension of shelf life of food products. LAB metabolism also contributes for the development of desired product properties such as flavor and texture [1,2]. Because of their long tradition of safe use (GRAS microorganism), their capacity to grow rapidly on lactose-based media derived from milk and their potential to generate a variety of metabolic products, LAB also have the potential to be used as cell-factories in bioreactors for the in situ production of compounds that contribute to the flavor, texture or health benefits of foods [1].
Among LAB, Lactococcus lactis is, by far, the most extensively studied with respect to its physiology, metabolic pathways and regulatory mechanisms, and its genome was the first LAB genome to be completely sequenced and annotated [3]. Lactococci are nutritionally fastidious organisms with a very limited biosynthetic capacity. Anabolic precursors are primarily imported from the growth media, whereas only a minor fraction is synthesized de novo from a carbon source. The major part of the carbon from carbohydrates is converted into fermentation end-products. For example, during growth on glucose, only about 5% of the metabolized sugar is converted into biomass [4]. The very limited biosynthetic capacity of L. lactis implies that, for optimal growth, they require exogenous supply of a fermentable sugar, numerous vitamins and amino acids, phosphate, potassium and magnesium [5].
L. lactis is a facultative anaerobic bacterium. Some strains are capable of growing in the presence of oxygen and adjust their metabolism accordingly, while others are strongly inhibited under aerobic conditions. As this microorganism lacks a functional respiratory chain, the ability to grow aerobically has been linked to the presence of NADH-oxidases. Since L. lactis is not able to perform respiration, ATP is only formed through substrate level phosphorylation. Thus, in order for Lactococci to grow at a high specific growth rate, a high carbohydrate degradation rate (and, concomitantly, an efficient sugar transport system) is called for. The main function of the sugar metabolism in L. lactis is to generate the energy necessary for rapid growth and for maintenance of intracellular pH during acidification of the environment [6].
Due to its major importance as a laboratorial and industrial microorganism, and because of its relatively simple metabolism and limited biosynthetic capabilities, L. lactis has been an organism of choice for many metabolic engineering purposes [1,6,7]. Hence, the design of enhanced metabolic engineering strategies calls for models where cellular behavior can be predicted.
The reconstruction of the entire metabolic reaction network of a cell and subsequent application of genome-scale flux models has been conducted for many organisms, including bacteria, yeast, fungi and animal cells [8-12]. These models have the potential to become common modeling tools. One approach that has been used to explore the capabilities of these large metabolic networks is flux balance analysis (FBA). This is simply a linear programming posed problem in which the constraints are defined by the stoichiometry of enzymatic reactions and transport steps. A solution to the problem, i.e., a set of fluxes through all the defined reactions, can be found through specifying an objective function, which is often defined as the optimization of a certain flux of interest, e.g., the flux towards formation of biomass. Maximization of biomass production has been shown to allow description of overall metabolic behavior in a number of cases, probably because most cells have evolved, under laboratory conditions, towards the maximization of their growth performance [13]. By using appropriate constraints and a meaningful objective function, FBA has been successfully used in exploring the relationship between genotype and phenotype and in the prediction of product yields and growth rates under changing environmental and genetic conditions, at steady state [14-16]. More recently, another approach has been proposed for dealing with the effect of gene deletions in the prediction of flux distributions, based on quadratic programming [17]. This minimization of metabolic adjustment (MOMA) approach relies on the assumption that optimal growth may initially not be true for mutants generated artificially in the laboratory as usually those mutants have not yet undergone evolution towards optimal growth.
In this work the reconstruction process of the metabolic network of L. lactis is presented. Network reactions were collected using the annotated genome sequence, biochemical and metabolic pathways databases, biochemistry books and journal publications. Once the network was established, FBA and MOMA were applied to analyze the network capabilities and to model phenotypic behavior under anaerobic and aerobic conditions. Simulation results were compared with experimental data available in the literature. Furthermore, the model was used to identify possible metabolic engineering targets to design an efficient diacetyl producing strain.
Results and discussion
Characteristics of the reconstructed network
The reconstruction process resulted in a network comprising 621 reactions and 509 metabolites. The entire reaction database can be consulted in the 1 and is also available at http://www.fluxome.com/models/Lactococcus_lactis.html webcite. A total of 358 ORFs out of the detected 2310 ORFs in the sequenced genome were considered, corresponding to 476 associated reactions. The remaining 145 reactions were included based on biochemical/physiological considerations or inferred by the demands imposed on the metabolic network. Namely, reactions were included based on experimental information reported in literature to account for pathway gaps, transport steps and biomass assembly. From the entire set of reactions, 492 correspond to intracellular reactions while 129 are transport fluxes over the cytoplasmic membrane. From the 358 ORFs considered, 63 ORFs account for genes that have been isolated and identified from L. lactis, 286 ORFs have high homology with identified genes from other organisms, 2 ORFs are annotated sequences derived from low level homologues and 7 ORFs are described as probable homologues of unknown function (ORF reliability classification based on [18]). The reaction database includes a total of 509 network metabolites, from which 414 are intracellular and 95 are external metabolites. 87 out of these 95 are metabolites secreted or taken up by the cell without undergoing phosphorylation, and so it can be pointed out that the reconstructed network accounts for 422 unique metabolites. Table 1 summarizes the main characteristics of the reconstructed metabolic network of L. lactis.
Additional File 1. List of reactions, ordered by metabolic pathway and alphabetically. List of reactions included in the metabolic network of Lactococcus lactis. Sheet "pathway_order" contains the reactions grouped by metabolic pathway, and journal references are indicated whenever reaction information is taken from journal references other than Bolotin et al. (2001). Sheet "alphabetic_order" lists the reactions alphabetically.
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Table 1. Main characteristics of the reconstructed metabolic network of Lactococcus lactis.
Network reactions
From the 358 ORFs considered in the reconstruction process, ORFs that are assigned to energy metabolism, amino acid biosynthesis and nucleotides metabolism account for more than half of the total number. These ORFs are involved in 476 reactions. The relatively high number of associated reactions is mainly due to the existence of low substrate-specific enzyme activities catalyzing different reactions. For instances, the model includes a low-specific aminotransferase (araT) involved in the metabolism of several amino acids and defined to catalyze 18 reactions in the model. An equation on biomass formation was developed to account for the drain of precursors and building blocks into biomass. A detailed description of its assembly can be found in the 2. This equation also accounts for energy requirements associated with growth, which have been estimated through model fitting against experimental observations as being 18.15 mmol ATP gDW-1. One reaction was included to account for non-growth dependent ATP maintenance. For growth under glucose limitation this value has been previously experimentally determined and equals 1 mmol ATP gDW-1h-1 [19].
Additional File 2. Biomass composition. Derivation of the equation for biomass composition, based on literature information.
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Network metabolites
The metabolic network of L. lactis contains 509 metabolites, 422 of which are unique metabolites. It is through metabolites that reactions are connected, as the product of one reaction becomes the substrate of another. At a zoom-out level, different biochemical pathways within a cell are interconnected by virtue of metabolites that participate in more than one pathway [20]. In particular, cofactors like ATP, NADH and NADPH play an important role in connecting the many different pathways. The most frequent metabolic intermediates in the reconstructed network are presented in Table 2. A total of 28 intracellular metabolites were not connected into the overall metabolic network. These non-connected metabolites take part in 25 "non-connected" reactions, catalyzed by 21 "non-connected" gene products (see 3)
Additional File 3. Non-connected Metabolites. List of the non-connected metabolites and reactions.
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Table 2. Connectivity of metabolites in Lactococcus lactis. Connectivity is defined as the number of reactions in which the listed metabolites participate in.
Growth requirements and minimal media
L. lactis is able to metabolize a variety of different sugars and other carbon sources [2,21] to obtain energy, redox power and precursor metabolites for macromolecular biosynthesis. Fermentable carbon sources utilized by L. lactis include fructose, galactose, glucosamine, glucose, lactose, maltose, mannitol, mannose, ribose, sucrose and trehalose.
The capabilities of the in silico model to utilize different carbon sources to grow were evaluated using FBA, using comparable uptake rates and carbon-limited conditions. All the above mentioned carbon sources were supplied, one at a time, together with all amino acids and nucleotides. A sugar consumption rate of 13.6 mmol gDW-1 h-1 was considered (6.8 mmol gDW-1 h-1 in the case of disaccharides), both under aerobic and anaerobic conditions.
The specific growth rate under anaerobic conditions was always higher than at aerobic conditions when the specific oxygen consumption was set to 3.61 mmol gDW-1 h-1 [22], which is in good agreement with experimental evidence [23]. The predicted anaerobic specific growth rate on glucose was 0.79 h-1, while the aerobic specific growth rate was 0.62 h-1. In case oxygen uptake is not constrained (unlimited oxygen uptake is allowed) the specific growth rate was 0.82 h-1. Constrained aerobic growth is slightly lower than anaerobic growth due to the different flux constraints applied to the enzymes that metabolize pyruvate into acetyl-CoA (see Methods). Pyruvate-formate lyase is only active under anaerobic conditions, while the pyruvate dehydrogenase (PDH) complex is only active during aerobic growth [24]. This forces the cell to produce more NADH under aerobic conditions, since the PDH complex is a NADH producing step and is also an essential reaction for formation of the precursor metabolite acetyl-CoA. However, model results indicate that for low oxygen consumptions there is a limited capacity to recycle NADH through NADH-oxidase, therefore causing the cell to reduce the flux through the PDH complex, decreasing the amount of acetyl-CoA available for lipid metabolism and, consequently, for biomass formation.
Growth on mannose, galactose, sucrose, lactose and glucosamine was found to be the same as for growth on glucose. The capacity to grow on trehalose and maltose was slightly higher, due to a decreased ATP requirement for the synthesis of the corresponding phosphorylated sugars. Anaerobically, growth on fructose and mannitol led to a decrease of 3% and 16% in biomass formation, respectively, compared with growth on glucose. This decrease has been qualitatively observed experimentally [21,25,26]. In the case of fructose, the difference seems to be associated with a lower capacity to generate NADPH due to a lower flux through the pentose phosphate pathway. In the case of mannitol, the lower biomass formation rate seems to be related both with a decrease in the capacity of generating NADPH and with a NADH burden due to formation of an additional NADH molecule during the reaction catalyzed by mannitol-1-phosphate dehydrogenase. Probably as consequence of that burden, the simulated growth leads to the production of high amounts of ethanol and formate, which is in good agreement with experimental results reported by Neves et al. (2002) [26].
In addition to a carbohydrate source, the minimal amino acid requirements were determined by omission of each amino acid at a time. The single omission of arginine, methionine and valine was found to prevent in silico growth, even when all other amino acids are supplied and despite the presence of the biosynthetic pathways for these amino acids in the reconstructed network. In the case of valine this result is trivial, since simulations were run under the constraint that the reaction catalyzed by bcaT_1 can only occur in the catabolic direction, and there is no alternative pathway for valine synthesis. In the case of methionine, the reason appears to be the lack of available FAD (cofactor) to sustain growth. Finally, if no arginine is supplied, the linear problem becomes infeasible. Nevertheless, arginine synthesis is observed when maximizing for an arginine drain.
Growth was not observed when only these three amino acids were supplied. If glutamate (or, alternatively, glutamine) is allowed to be taken up in the presence of these three amino acids, growth occurs. Therefore, glucose, arginine, methionine, glutamate (or glutamine) and valine were found to be the minimal required medium for growth. L. lactis strains are usually auxotrophic for 7 to 9 amino acids, including these four [5,27]. Growth in the above defined minimal media is, however, 54% lower than in rich media. When all the amino acids reported as essential for L. lactis IL1403 [27] are allowed to be taken up by the model, growth rate increases to 87% of the value in rich media. This corresponds to the addition of asparagine, histidine, isoleucine and leucine to the above defined minimal media.
Single gene deletion analysis
Single gene deletion analyses were computed to predict the lethal effect of deleting each individual gene. Prediction capability was assessed by comparing simulation results with experimental data on gene lethality reported for L. lactis [28] and Bacillus subtilis [29], a related Gram-positive bacteria of low G+C content, during growth in rich media. 25 genes were found in literature as being lethal, out of the 34 predicted by the model. From these, one is a false lethal (ThyA), while no references were found for the remaining 8 (see 4). Regarding these analyses, it has to be point out that regulatory proteins and constrains were seldom included, so it is likely that we are underestimating the number of actual lethal genes.
Additional File 4. Single gene and reaction deletions. List of genes and reactions from the metabolic network found to be lethal, ie, no growth was observed when setting the corresponding flux to zero and applying FBA or MOMA. Results are described both under anaerobic and aerobic conditions and both during growth on rich and minimal media.
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The effect of the deletion of each reaction was also assessed. These computational studies were performed both in rich media and minimal media, and both under aerobic and anaerobic conditions. FBA and MOMA were used to compute these simulations, with MOMA predicting around 10 more lethal genes/reactions than FBA (Table 3). We focus the following analysis on MOMA results (all details can be found in the 4). The deletion of 24.6% of the genes showed to be lethal in minimal media, while in rich media this number decreases to 12.1% (percentage based on the number of ORFs included in the model, discounting the 21 "non-connected" gene products). The single deletion of reactions accounts for 23.1% lethal reactions in minimal media and 14.1% in rich media (considering 596 network reactions: all the 621 network reactions minus the 25 "non-connected" reactions). Additionally, it was observed that although the number of lethal reactions is always higher than the number of lethal genes, this is mainly due to the existence of reactions catalyzed by unknown gene products (enzymes without a corresponding annotated ORF).
Aerobic and anaerobic simulations led to similar results, with a few more genes/reactions being lethal under aerobic conditions, namely those associated to oxygen utilization, CO2 production and to the pyruvate dehydrogenase (PDH) complex. Under aerobic conditions, the PDH complex is the only pathway leading to the formation of acetyl-CoA from pyruvate, and as acetyl-CoA is an essential metabolite in many processes (such as lipid formation), deletion of the PDH complex results in a lethal phenotype.
When comparing the growth capabilities in both rich and minimal media, it can be observed that approximately 40 additional genes are lethal during growth in minimal media. These are mainly genes associated with biosynthesis of amino acids. From the 83 lethal genes in minimal media, 19 encode for gene products that catalyze more than one reaction. Only one of these 83 genes encoded for a protein that has an isoenzyme.
Modeling the shift from homolactic to heterolactic metabolism
To further evaluate the modeling capabilities of FBA we used the genome-scale flux model to simulate the shift from homolactic to heterolactic metabolism in L. lactis growing anaerobically. This process consisted in comparing simulation results with experimental observations reported by Thomas, T.D. et al. (1979) [30] for glucose limited anaerobic chemostat cultures, though refining and tuning the model through the introduction of appropriate biological meaningful constrains. Nevertheless, one should notice that although FBA is based on steady-state assumption and therefore is more suitable for simulation of metabolic behavior in continuous cultivations, model results can also be compared with batch experimental data under the assumption of pseudo steady-state during the exponential growth phase.
Experimental observations reported in literature suggest that, for L. lactis, product formation at high dilution rates during continuous cultivations is similar to product formation during batch growth at high glucose concentrations, resulting in lactic acid as the sole metabolic product [19,31]. On the other hand, growth at low dilution rates in continuous conditions or at low concentrations of glucose in batch conditions (ie, in the presence of low fluxes through glycolysis) results in a mixed-acid fermentation, where formate, ethanol and acetate are produced in a molar ratio of 2:1:1 [32]. While indicating that the shift in metabolism is due to regulation, these observations also suggest that different flux constraints would have to be introduced to model the shift from homolactic to heterolactic metabolism.
For simulations of phenotypic behavior, the first obvious objective function was thought to be "maximization of growth" while constraining for substrate uptake. However, it became clear that constraining values for amino acid uptake rates would pose a problem, as the in silico strain was auxotrophic for some amino acids, which could act as a carbon source, and no information was found available in the literature for amino acid uptake rates under chemostat conditions. To solve this problem, consumption rates were approximated to be equal to the amino acids requirement for biomass formation. In the absence of experimental information for amino acid uptake rates another approach was followed, in which phenotypic behavior was simulated by constraining the growth rate and minimizing for substrate uptake. Both approaches led to different and complementary qualitative results regarding the network capabilities, as discussed below.
Maximizing for growth
When maximizing for biomass formation, the metabolic phenotype cannot be correctly predicted from the reconstructed network by simply stating anaerobic constraints (see Methods). The process of tuning and refining the model is discussed below and detailed results are summarized in Figures 5 and 6 (see 5). Simulations in which the specific consumption rate of glucose was constrained to values equal or greater than 14.1 mmol gDW-1 h-1 revealed the occurrence of multiple solutions for products of metabolism. From these simulations it was observed that growth rate does not change with different glucose uptake rates, indicating that growth is nitrogen-limited and reaches a maximum at 0.82 h-1 (in good agreement with the fact that amino acid uptake rates were established based on the amino acid cell content at 0.8 h-1), while for glucose uptake rates lower than 14.1 mmol gDW-1 h-1 growth is glucose-limited. Since lactate production is reported under high glycolytic fluxes, and this is known to be due to regulation exerted by the NADH/NAD+ ratio on the pyruvate-formate lyase [33], additional constraints can be included in the model in order to account for regulatory information. For example, Covert, M.W. et al [34] described a Boolean on/off approach to account for regulation within the metabolic network. However, since pyruvate-formate lyase is essential to the formation of acetyl-CoA (and therefore, biomass) under anaerobic conditions, a simple on/off Boolean statement cannot be applied. Therefore, based on fitting the model against experimental data, the pyruvate-formate lyase flux was set to 2.15 and 9.8 mmol gDW-1 h-1 to simulate homolactic growth when glucose uptake rates equal 24.6 and 18 mmol gDW-1 h-1, respectively.
Additional File 5. Modeling the shift from homolactic ot heterolactic metabolism. These tables summarize the modeling procedure for inclusion of appropriate constrains when applying FBA to simulate anaerobic growth.
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In all simulations it can be observed that the metabolic model predicts trace production of amino acid catabolism products (3-methyl-2-oxobutanoate, 3-methyl-2-oxopentanoate, 4-methyl-2-oxopentanoate, phenyllactate, methional), which is in good agreement with experimental results [35-37]. Interestingly, it can be observed that although the formation of these catabolic products is not directly accompanied by the formation of energy or reduced compounds, they all contribute to a gain in biomass formation.
Plotting experimental against model results for biomass, lactate, formate, ethanol and biomass formation (Figure 1) shows that simulations can reproduce the general observed tendencies for product and biomass formation, overestimating biomass formation. Also formate, ethanol and acetate are slightly overestimated for the range of the simulated conditions. At high glucose uptake rates, the model cannot predict the absence of these products. From Figure 1 it can further be observed that lactate production is poorly described with the considered constraints. Additional constraints could have been introduced to better describe lactate formation. However, this imposes too many uncertain variables, namely for amino acid consumption.
Figure 1. Plotting model and experimental data for anaerobic growth, chemostat conditions, when maximizing for biomass formation. Growth rate and conversion yields for lactate (L), formate (F), ethanol (E) and acetate (A) on glucose (S) are plotted against glucose uptake rate. Model results are from simulations NX5 to NX10 (see Table 5 in 5). Experimental data is from Thomas, T.D., et al (1979) [30]. Ethanol and formate predictions are overlapped.
Minimizing for substrate uptake
To overcome this difficulty another approach was used: the minimization of substrates uptake while constraining the growth rate. From simulation results, the formation of end-products of the pyruvate metabolism is observed. No by-products from the amino acid catabolism were predicted using this approach, as it minimizes amino acids uptake, and therefore no excess of amino acids is available for catabolism of amino acids. Without further constraints, mixed-acid fermentation is observed, as this is energetically more favorable for the cell (more ATP is formed when acetate is synthesized). However, as mentioned above, high fluxes through glycolysis lead to regulation effects towards homolactic fermentation. Consequently, the reaction catalyzed by pyruvate-formate lyase was constrained to values between 0 and 9 mmol gDW-1 h-1 (see Table 6) by fitting simulation results against experimental data
From Figure 2 it is observed that model results for formate, ethanol and acetate formation fairly fit experimental observations, although the model underestimates ethanol and acetate production and overestimates formate production. Furthermore, glucose consumption is also underestimated by model predictions. The difference is around 14% at high substrate uptake rates and 25% for lower values. This can be due, for example, to differences in the maintenance energy between the real cell and the simulated system.
Figure 2. Plotting model and experimental data for anaerobic growth, chemostat conditions, when minimizing for substrates uptake. Glucose uptake rate and conversion yields for lactate (L), formate (F), ethanol (E) and acetate (A) on glucose (S) are plotted against growth rate. Model results are from simulations NS3, NS5, NS7, NS8 to NS11 (see Table 6 in 5). Experimental data is from Thomas, T.D., et al (1979) [30]. Acetate and formate predictions are overlapped.
Analysis of amino acid requirements for in silico growth interestingly shows that, for most of the cases, amino acid uptake rates linearly increase with the growth rate (Figure 3). This observation only applies if metabolic families of amino acids, derived from the same precursor, are considered. Threonine was included in the serine-family (instead of the expected aspartate-family), as it is related with glycine through the reaction L-threonine <-> glycine + acetaldehyde. Even with this change, linearity is not observed for both these families. Two reasons can be hypothesized to explain that: either threonine synthesis pathway depends on the growth rate or, alternatively, it is the serine contribution for the pyruvate pool that depends on biomass formation rate.
Figure 3. Model predictions for glucose and amino acid uptake rates versus the growth rate. Model results are from simulations NS3, NS5, NS7, NS8 to NS11. Amino acids were grouped into six families: Histidine (His), Aromatic (Phe, Trp, Tyr), Serine-family (Cys, Gly, Met, Ser, Thr), Pyruvate-family (Ala, Ile, Leu, Val), Aspartate-family (Asp, Asn, Lys) and Glutamate-family (Arg, Glu, Gln, Pro) [47].
When minimizing for substrate uptake, the predicted amino acid uptake rates corresponds to the theoretical amino acid requirements for the cell to grow at the established growth rate. However, in vivo amino acids consumption is usually higher than the theoretical needs for macromolecules biosynthesis. The excess of amino acids can then be further catabolized, resulting in the secretion of amino acid by-products.
Amino acid biosynthesis capabilities
In all simulations under the objective of minimizing the substrate uptake, it could be noted that some amino acids are not taken up from the medium even if they are present in the medium. The cell seems to prefer to synthesize some of them. Amino acids completely synthesized by the in silico strain were alanine, aspartate, glycine and phenylalanine (either if glutamate is or is not supplied). Remarkably, this observation is in very good agreement with experimental data reported by Jensen, N.B. et al. (2002) [38] for L. lactis subsp cremoris. In their work, they analyzed the capacity for the de novo biosynthesis of amino acids when all amino acids except glutamate were supplied, having observed that alanine, aspartate, phenylalanine and threonine, were synthesized de novo by the cell. Analyzing the flux distribution of the reactions involved in amino acid biosynthesis, it can be found that those preferences are associated with an increased production of 2-oxoglutarate, leading to an increased formation of L-glutamate.
Identfication of metabolic engineering targets
A relevant application of genome-scale metabolic models is the simulation of cellular behavior in response to genetic perturbations. Namely, genome-scale metabolic models can be used as tools in the design of metabolic engineering strategies, aiming at finding genetic targets leading to enhanced desired properties [20]. We exemplify here the use of the reconstructed network to predict potential ways to increase the yield of diacetyl, an important flavor compound in dairy products. Diacetyl is a by-product of L. lactis fermentative metabolism and it is produced chemically by oxidative decarboxylation of the metabolic intermediate 2-acetolactate (which is derived from the condensation of two molecules of pyruvate). Hence, knockout strategies leading to an increased yield of 2-acetolactate in glucose were investigated using FBA and MOMA.
Lactococci metabolism around pyruvate is depicted in Figure 4. From pyruvate, carbon can be redirected towards acetyl-CoA, lactate or 2-acetolactate. Common strategies to increase the flux towards 2-acetolactate have been gene knockouts around pyruvate (except of the lethal pyruvate dehydrogenase complex), over-producing the 2-acetolactate synthase and/or over-producing an heterologous NADH-oxidase [1,7,39-41]. For example, Henriksen et al (2001) [24] have succeed to convert up to 95% of glucose towards the formation of 2-acetolactate and related compounds through the deletion of lactate dehydrogenase and pyruvate-formate lyase. Hugenholtz et al (2000) [39] constructed a high-producing diacetyl strain able to redirect 80% (16%) of glucose into 2-acetolactate (diacetyl), by deleting acetolactate synthase and over-expressing an heterologous NADH-oxidase.
Figure 4. The pyruvate metabolism of Lactococcus lactis. LDH: lactate dehydrogenase; PDH: pyruvate dehydrogenase complex; PFL: pyruvate formate-lyase; ADHE: acetaldehyde dehydrogenase ; ADHA: alcohol dehydrogenase; PTA: phosphotransacetylase; ACKA: acetate kinase, ALS/ILV B: catabolic and anabolic 2-acetolactate synthase; ALDB-acetolactate decarboxylase; BUTA-diacetyl reductase; BUTB: acetoin reductase; NOX: NADH – oxidase. ..
The first step in our modeling strategy was to find a set of appropriate constraints that lead to results comparable with experimental observation. By simply allowing unconstrained uptake of oxygen it was possible to obtain both 2-acetolactate and acetate as the main by-products of metabolism, which is in good agreement with experimental reports [39]. Oxygen uptake was about 1.4 mmol O2 / mmol glucose. The simulated growth rate and yield of 2-acetolactate on glucose are presented in Table 4. However, a plurality of solutions were observed under the chosen conditions. In order to minimize the number of solutions, we constrained the activity of lactate dehydrogenase (ldh), 2-acetolactate synthase (aldB) and alcohol dehydrogenase (adhA) to zero. This forces pyruvate to be redirected either towards acetate or 2-acetolactate (and related compounds, ie, C4 and C5 products).
Table 4. Designed strategies to enhance 2-acetolactate production, and corresponding predictions for specific growth rates and yields of 2-acetolactate on glucose.
Next, the impact of single gene deletions on product formation was simulated by maximizing for growth. It was found that the deletion of PTA leads to a slight yield increase. The enzyme Pta catalyzes the conversion of acetyl-CoA to acetyl-P, and its deletion eliminates the production of acetate. Furthermore, another single gene deletion was run on the "mutant" ΔldhΔaldΔadhAΔpta and three deletions leading to a higher production of 2-acetolactate were found, ΔFHS, ΔSERA and ΔZWF. The enzyme Fhs is a formyltetrahydrofolate synthetase (EC 126.96.36.199), involved in the folate metabolism. Its contribution towards a higher yield of 2-acetolactate is due to an increase in carbon availability for by-product formation, since this reaction is used by the cell to generate ATP and formate (in rich media). The enzyme SerA, a 3-phosphoglycerate dehydrogenase, is involved in serine metabolism. This part of the metabolism connects with Fhs. Hence, this deletion increases 2-acetolactate yield similarly to the deletion of SERA. Finally, ZWF deletion is only predicted by MOMA as being advantageous. ZWF encodes for glucose-6-phosphate 1-dehydrogenase, the first step of the pentose-phosphate pathway. This deletion is accompanied by a decrease in biomass formation, because the availability of NADPH decreases. Therefore, more carbon is redirected towards other products of metabolism (C4 and C5 compounds), resulting in an increase of 2-acetolactate yield. Observed yields and biomass formation rates are summarized in Table 4. One should keep in mind that these are theoretical maximum specific growth rates at which high yields of 2-acetolactate can be obtained. Other factors such as a limitation in the uptake rate of oxygen may lead to experimentally lower values.
The metabolic network of Lactococcus lactis was reconstructed based on genomic, physiological and biochemical information, comprising a total of 621 reactions and 509 metabolites. Lactococcal network characteristics are comparable with other bacterial genome-scale reconstructed networks.
Metabolic network analysis was carried out using FBA and MOMA. The genome-scale metabolic model for L. lactis was shown to be robust and able to predict many experimental observations, when considering additional constraints derived from available experimental data. The model proved to be a useful tool to analyze the metabolic capabilities of L. lactis and to understand how the individual components in the system interact and influence the overall cell function. For example, the model could predict that, if all the amino acids were supplied, the cell will prefer to synthesize de novo alanine, aspartate, glycine and phenylalanine. The model can now be used as a useful tool to test or develop novel metabolic engineering strategies to redirect fluxes towards the production of important products such as diacetyl, alanine and exopolysaccharides [1].
Reconstructed metabolic networks are finding many other applications than the ones described in this work. Optimization methods have also been used to assess maximum capabilities of the network and to analyze gene dispensability [42]. More recently, different methods to integrate metabolic networks with transcriptome data were described [43-45]. Patil and Nielsen (2005) [45] describe a method that represents the metabolic network as an enzyme-metabolite interaction graph and, assigning expression scores to each enzyme, it is possible to highlight which metabolites are more affected by transcriptional changes (the so-called reporter metabolites). The method also identifies the most active metabolic sub-network responding to a particular perturbation. In the near future it is expected that metabolic networks will be further used together with other types of 'omic' information and help to reveal hidden information on cellular organization and function.
Network reconstruction
The reconstruction process of the metabolic network of L. lactis involved a comprehensive search of the current knowledge of its metabolism. The process started based on the ORFs information from the annotated genome of L. lactis IL 1403 [3]. From this list, a reaction database was built using the available genomic, biochemical and physiological data accessible in databases and relevant literature. Particular focus was given to the reactions reversibility. Reactions whose reversibility could not be assessed were defined as reversible. The reaction set also includes a reaction for biomass formation defined as a drain of major building blocks into biomass. One reaction was included to account for non-growth dependent ATP maintenance. After the initial assembly of the entire metabolic network, the list was re-examined to account for metabolic and physiological details. The list of reactions was manually and carefully examined regarding reliability of gene assignment, all possible/probable catalytic activities of gene products and the in vivo reaction reversibility.
Biomass composition
An equation for biomass formation was developed to account for the drain of precursors and building blocks into biomass. Biomass synthesis was set as a linear combination of seven macromolecular components – proteins, DNA, RNA, lipids, lipoteichoid acids, peptidoglycan and polysaccharides – which were considered to account for the cell overall biomass composition. The individual composition of every component was maintained at a fixed stoichiometry, independent of the specific growth rate. Cellular energy requirements were also considered, by taking into account information on the ATP cost of polymerisation and growth and non-growth associated ATP maintenance. The detailed calculation of the biomass composition can de found in the 2.
From the developed equations, an elemental biomass composition was determined for the reconstructed in silico strain, CH1.95O0.63N0.22P0.02S0.01, corresponding to a molecular weight of 27.8 g/C-mol. This is in good agreement with values found in the literature. Novak, L. et al. (2000) have measured a value of 27.7 g/C-mol for L. lactis.
Mathematical frameworks: FBA and MOMA
Flux balance analysis (FBA) is a linear programming posed problem where equations are defined by mass balance-derived stoichiometric reactions, constrains are imposed by fluxes limitations and the objective function is established based on a biological meaningful objective.
Given a stoichiometric matrix derived from mass balance around all metabolites of a cell and assuming steady state, a system of linear equations is produced which simply states that the incoming fluxes are balanced by the outgoing fluxes. For a metabolic network comprising N metabolites and M metabolic reactions, the stoichiometric matrix can be written as:
where Sji is the stoichiometric coefficient of metabolite j in reaction i, vi represents the flux of reaction i, and bj quantifies the network's uptake (or secretion) of metabolite j. Reversible reactions are defined simply as two irreversible reactions in opposite directions, constraining all fluxes to nonnegative values, ie:
vi ≥ 0, ∀ i (2)
Some other constraints based on physiological or physicochemical aspects may be applied, such as thermodynamics considerations, regulation effects and maximal enzymatic rates:
α ≥ vi ≥ βi, ∀ i (3)
Establishing a particular objective function, Z, written as a linear combination of existing variables, the optimal solution can then be found at one corner of the set of feasible solutions. For metabolic applications, typical objective functions are maximization of biomass formation or minimization of substrate consumption.
Flux balance analysis can then be simply summarized as a linear programming problem posed as:
maximize Z = eg, biomass formation (4)
subject to
vi ≥ 0, ∀ i
α ≥ vi ≥ βi, ∀ i
Another mathematical framework that can be used to find flux distribution solutions is the so-called minimization of metabolic adjustment (MOMA) [17]. MOMA relaxes the assumption of optimal growth flux for gene deletions, displaying a suboptimal flux distribution that is intermediate between the wild-type optimum and the mutant optimum. The philosophy of MOMA can be interpreted as the projection of the FBA optimum onto the feasible space of the mutant. Therefore, MOMA can be posed as a quadratic programming problem, with the same set of linear constrains as for FBA and where the objective function is to minimize the distance between the feasible solutions space of both wild-type and mutant.
Both the FBA and the MOMA problems were solved with an in-house developed software using the following solvers: GNU Linear Programming Kit http://www.gnu.org/software/glpk/glpk.html webcite and Object-Oriented software for Quadratic Programming http://www.cs.wisc.edu/~swright/ooqp/ webcite.
Model constraints
All simulations were run allowing free uptake of nucleotides (xanthine, uracil, cytosine, adenine, guanine and hypoxanthine), phosphate, biphosphate and sulfate. Additionally, non-growth associated ATP requirement was always set to 1 mmol ATP gDW-1 h-1, which is the value experimentally estimated for carbon-limitated chemostat cultures [19].
To simulate growth under anaerobic conditions, the oxygen uptake rate was set to zero. Experimental insight on pyruvate metabolism led to two additional constraints. Since it is known that the pyruvate dehydrogenase (PDH) complex is not active in the absence of oxygen [46], pdhA_1 and pdhB_1 fluxes were therefore set to zero.
Aerobic growth was simulated by allowing oxygen to be taken up by the model. Unless otherwise stated, the oxygen consumption was set to 3.61 mmol gDW-1 h-1 [22]. Under aerobic conditions the pyruvate dehydrogenase is active but the pyruvate-formate lyase (PFL) is strongly inhibited by oxygen [24]. pdhA_1 and pdhB_1 were therefore left unconstrained while the pfl_1 flux was set to zero.
Evaluation of growth requirements and minimal media
Network capabilities to utilize different sugar sources were evaluated using FBA. A number of different sugars were supplied, one at a time, together with all amino acids and nucleotides. A sugar consumption rate of 13.6 mmol gDW-1 h-1 was allowed, both under aerobic and anaerobic conditions (6.8 mmol gDW-1 h-1 in the case of the disaccharides sucrose, lactose, maltose and trehalose). When the specific growth rate was higher than 0.01 h-1, the sugar was considered to be used for growth. This value was established based on the observation that when supplying only amino acids but no sugar, a specific growth rate of 0.01 h-1 is predicted by the model, which is not observed experimentally [19].
Amino acid requirements for in silico cell growth were analyzed under anaerobic conditions. The dilution rate was fixed to 0.18 and 0.76 h-1 and the objective function used in this investigation was the minimization of substrates uptake rate. Beginning with all the amino acids available, single-omissions were simulated by setting the corresponding uptake rate to zero, one at a time. If no biomass is formed, the omitted amino acid was defined as essential for growth. Simulations were run with the reactions catalyzed by bcaT_1, bcaT_2 and bcaT_3 constrained to the catabolic direction.
A minimal medium was established by allowing uptake of glucose at a rate of 13.6 mmol gDW-1 h-1 and uptake of the previously determined essential amino acids at a rate of 0.5 mmol gDW-1 h-1 per amino acid. Remaining amino acids were individually supplied until growth was observed.
Single gene/reaction deletion analyses
Single gene deletion (SGD) and single reaction deletion (SRD) analyses were performed using both FBA and MOMA. Reaction deletions were simulated by setting the corresponding flux to zero. Gene deletions were simulated by setting to zero all fluxes catalyzed by the corresponding gene product. Lethality was evaluated based on the deletions that led to infeasible problems or to biomass formation lower than 0.01 h-1. For simulation of growth on rich media, glucose uptake was set at 13.6 mmol gDW-1 h-1, and all amino acids were allowed to be taken up (at a rate corresponding to the amino acid cell content assuming a specific growth rate of 0.8 h-1). Simulating growth on minimal media, only glucose at 13.6 mmol gDW-1 h-1, arginine, methionine, valine and glutamante (0.5 mmol gDW-1 h-1) were supplied.
Modeling of homolactic and heterolactic metabolism
The shift from homolactic to heterolactic metabolism was simulated under anaerobic conditions, using FBA. Appropriated flux constraints were determined by fitting the model to experimental results, which is described in the following.
Two different approaches were selected to predict cell growth and product formation. First, glucose and amino acid uptake rates were set to fixed values and biomass production was maximized. Growth rate and products formation were determined as a function of different glucose uptake rates. Values for sugar uptake rates were taken from the literature [4,30], ranging from 7 to 24.6 mmol gDW-1 h-1. Amino acids uptake rates were calculated from the amino acid cell content assuming a specific growth rate of 0.8 h-1 [4]. A second approach consisted of setting a fixed specific growth rate while minimizing for the substrate uptake rates (objective function written as a linear combination of glucose and amino acids uptake rates, all terms with coefficient one). In this case, uptake rates and product formation were calculated for different specific growth rates. Here, a constraint on the flux of the pyruvate-formate lyase had to be introduced to account for experimental evidence, as suggested by Melchiorsen et al. (2002) [31].
Design of a diacetyl overproducing mutant
Simulations were performed under aerobic conditions and on rich media (as described above), with glucose as the carbon source (13.6 mmol gDW-1 h-1). Pyruvate secretion was not allowed and oxygen uptake was unconstrained. In silico gene deletions were simulated by constraining the respective fluxes to zero and solving the FBA problem while optimizing for biomass. Single gene deletions leading to high 2-acetolactate formation rates while allowing for growth (specific growth rate higher than 0.01 h-1) were selected as targets for metabolic engineering, as described in the Results and discussion section.
List of abbreviations
LAB: Lactic Acid Bacteria
GRAS: Generally Recognized As Safe
FBA: Flux Balance Analysis
MOMA: Minimization Of Metabolic Adjustment
ORF: Open Reading Frame
PDH: Pyruvate dehydrogenase
PFL: Pyruvate-formate lyase
Authors' contributions
APO carried out all aspects of the work and drafted the manuscript. JN conceived of the study and participated in its design and coordination. JF participated in the analysis of simulation results, conceived of the study, participated in its design and coordination and helped draft the manuscript. All authors read and approved the final manuscript.
Mats Åkesson is acknowledged for fruitful discussions on modeling issues and results. Kiran R Patil is acknowledged for developing a program to perform single gene/reaction deletion using FBA and MOMA. Karin Hammer is acknowledged for contribution on insights of gene lethality in L. lactis.
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text:
SPRINGFIELD, Ill. (AP) - Even though he's under pressure to resign, experts say that shouldn't keep Illinois Sen. Roland Burris from serving his constituents while he holds on to the seat.
Burris can vote as normal and serve on committees. He can also help constituents navigate through government bureaucracy and may still be able to bring home money.
Fellow Illinois Sen. Dick Durbin is among those calling for Burris to step down. But he's promising to "find ways to cooperate and work" with Burris. Durbin says he doesn't want the people of Illinois to lose anything because of the controversy over Burris.
Burris was appointed by former Gov. Rod Blagojevich just before the state legislature threw Blagojevich out of office over allegations he tried to sell the Senate appointment. Burris has revised his story of his contacts with the former governor and his aides, including acknowledging he looked into raising money for Blagojevich.
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It's easier than you think to eat well and save money. Here are 8 tips to live by.
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text: US Suffers a Mass Killing Every 2 Weeks 'USA Today' analysis returns surprising stat By Kate Seamons, Newser Staff Posted Dec 19, 2012 10:55 AM CST STORY COMMENTS (75) (Newser) – The Newtown killings have jolted the nation—and USA Today offers a stat that's bound to do the same. Its analysis of FBI records from 2006 to 2010 shows that a mass killing occurs in our nation, on average, every two weeks. It defines mass shooting as the FBI does, as one in which at least four people are murdered. Over those five years, 156 such attacks occurred, killing 774; at least 20% of those victims were under the age of 13. Among its other findings: About 25% of the attacks featured multiple killers A third involved no guns; fire, knives, or blunt objects were among the alternate murder weapons These killers are older than the typical murderer: average age is 32 Still, mass murders make up just 1% of all murders that occurred over the period. USA Today notes that, per CDC records, migraines and falls out of chairs killed more people. Click to see a chart of all 196 fatal school shootings that have occurred in America since 1980. Greg Frattaroli, 19, of Newtown, Conn., visits a memorial for the Sandy Hook Elementary School shooting victims, Tuesday, Dec. 18, 2012, in Newtown, Conn. (AP Photo/David Goldman) ADVERTISEMENT(Click Prev or Next to continue viewing images.) « Prev« Prev | Next »Next » Slideshow USA Today (Source Grid ») Crime & Courts • US school shooting • mass murder • Newtown, Connecticut • Connecticut school shooting CLICK BELOW TO VOTE 8% 5% 19% 21% 5% 41% RETURN TO THE STORY To report an error on this story, notify our editors.


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Growing up in the country, you could tell when the bluegill were about to start biting by the appearance of lightning bugs.
Later, when the katydids began to strum their mid-summer chorus, that meant it was time to forsake the scorching daytime heat and go night-fishing and frog-hunting.
Earlier this spring a late-evening drive to Reelfoot Lake brought back a lot of memories. As we motored along through the countryside, the dark, rolling fields glittered and twinkled like millions of Fourth of July sparklers.
Scientists theorize that lightning bugs – or fireflies – flicker on and off to attract admirers of the opposite sex.
Back in my prom-going days I owned a day-glow Leisure Suit that was supposed to do the same thing. I hope the lightning bugs have more success than I did.
As for katydids, there's nothing more nostalgic than listening to their endless debate on a hot summer night:
"Katy did!"
"No she didn't!"
"Katy did!"
"No she didn't!"
When I was a kid we didn't have a choice about listening to the summertime katydids. "Air conditioning" meant opening a bedroom window or sitting on the front porch until the evening cooled off.
Sometimes now, when the katydids start their serenade, I catch myself listening for the creak of the porch swing or the contented sigh of my old dog Kazan who always snoozed at my feet.
The katydids also stir memories of my boyhood buddies Ralph, Tommy, Tony and me tramping across pastures to farm ponds that glistened like silver pools in the moonlight.
Bass lurked in the shallows, ready to pounce on a Hula Popper or Jitterbug as it gurgled along the surface. There's noting more exciting than casting a top-water lure out into the misty darkness, retrieving it with a glug-glug-glug, and – ker-splash! – a big bass suddenly torpedoing it.
Like the burst of adrenaline that comes when a covey of quail suddenly explodes under your feet with a whirr, a top-water bass strike always startles the daylights out of you – and double-so in the dark.
And then there was frog hunting. I was reminded about how much fun frog-hunting used to be by a recent PETA protest of a frog hunt by some area kids. As I wrote at the time, we ought to be delighted that kids are outdoors hunting frogs and getting some exercise instead of plopped on a sofa turning themselves into I-Pad zombies.
Frog hunting is not just about going out to collect frogs, any more than going camping is going out just to sleep on the ground. It's about a band of teenaged buddies stomping around marshy banks while exchanging theories about high school, driver's permits, Mary Sue Wattenbarger and other cosmic mysteries.
The sweet smell of new-mown hay hangs in the warm summer night as lighting bugs flicker (looking for their own Mary Sue Wattenbarger?) and the keen of katydids is so loud that it makes your ears ring.
Occasionally a bullfrog joins in, singing bass, and off in the distance a whip-poor-will whistles a mournful dirge for someone who is about to pass on (so an old wives-tale claimed.)
Such mid-summer memories are only a firefly-flicker or a katydid away.


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Sport Science: Teacher Licensure
The Bluefield College Sport Science: Teacher Licensure major prepares students for careers in teaching Health and Physical Education at the Pre-K through 12 levels. The program is designed to prepare competent, caring and qualified teachers who are reflective practitioners. For the past 26 years, Dr. Scott C. Bryan, II has chaired the program that has graduated highly qualified teachers. These graduates serve in distinctive careers as teachers, coaches and administrators in public and private schools throughout Virginia and the United States. Their schools and communities have richly benefited from their service and leadership.
The Sport Science: Teacher Licensure is offered through the Exercise and Sport Science Major.
View the Exercise and Sport Science Major Page


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Linden's Quadri Moore, shown going to the basket on March 16, will be a key part of the Tiger's strategy in the Tournament of Champions.
- Filed Under
A season full of accomplishments would make any team happy, but the Linden High School boys basketball team is looking to fill a hunger for winning that never seems to subside.
A Union County Tournament championship and a Group IV state championship are all checked off of the Tigers' to-do list, but the aim is now set higher as they take on Pitman in the Tournament of Champions starting on Tuesday night.
"We're playing real well," said Tigers head coach Phil Colicchio. "We're playing hard and getting the ball to the right spots. We've gotten better offensively and we're just trying to keep ...


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SAISD BOND PROJECT: School's out, though classwork remains
Construction stays in session at 9 campuses
SAN ANGELO, Texas - A line of a dozen men wearing protective back braces wound its way across the springy dance floor and past the wall of mirrors in the TexAnns' future practice room.
Each man pushed a dolly loaded with boxes destined for the art, journalism and debate classrooms of the renovated Schweitzer Hall at Central High School.
"The only thing that was left in this building was the exterior brick walls," Steve Van Hoozer said this past week.
The director of San Angelo ISD's bond projects and construction said Schweitzer Hall is scheduled to be ready for students when they return in August, part of the renovation of the 2,000-student campus that is the largest part of the $117 million bond passed by voters in 2008.
The hall named after the 1952 Nobel Peace Prize winner Albert Schweitzer was the former home of the school's science labs and classrooms.
Updated science labs and classrooms now are housed in the largest construction project of the bond, the 72,000-square-foot Tucker Hall, which opened last fall at Central.
Tucker also is the administration building and the new, north-facing front entry of the campus.
While construction has continued year-round at Central for the past two school years, it ramps up during the summers when the campus can be closed to all except construction workers.
That has affected summer school, Principal Bill Waters said.
"We usually swap summer school between Central and Lake View High School, with one campus hosting it each year, but with the construction, we decided it would be best to have summer school at Lake View," Waters said. "We haven't had summer school at Central for three years."
Instead, contractors of all types and laborers swarm over the campus.
In addition to Schweitzer, Van Hoozer is hoping to see work completed on Michelangelo Hall, which will become the student service center and the choir practice facility, as well as on the newly renamed Banneker Hall I and II, which were the former administration offices and counseling center.
Banneker I and II will house special education classrooms and behavior modification classrooms and facilities, as well as two computer labs.
The original Banneker Hall, as well as Fulton Hall, Morse Hall, Emerson Hall and the Caddo Art building, have been demolishedto make room for Tucker Hall and adjacent parking lots.
The cafeteria, known as Mark Twain Hall, is getting completely rebuilt, Van Hoozer said.
Among the changes, small restrooms at the south end of the building have been demolished and will be replaced by larger restrooms at the north end.
The cafeteria also will get new, shaded outside seating for dining or for students waiting for the school bus, Van Hoozer said.
Next up for renovation is Holmes Hall, which Waters said is known as the "senior hall" because it houses such classes as junior and senior English language arts and government.
Renovation of Holmes is scheduled to be completed by Christmas.
"We're moving all those teachers out, most of them to Handel Hall and some to Tucker," Waters said.
Van Hoozer said Handel also is scheduled to be demolished but is being used as temporary housing for the classrooms ousted by renovations.
"Nearly everybody on campus will get to be in Handel at one point or another," he said.
Another big change students and teachers will see in August will be landscaping, new parking and emergency access roads.
"By the end of this summer, I think there will be a huge transformation at Central, and the next summer, hopefully, we'll be working on the final transformation," Van Hoozer said.
A big change at Central and the 10 other bond campuses is an increase in computer labs.
"Computer labs will be needed if online testing becomes required," Waters said. "The state is pushing to go to online testing. It's difficult. We're never going to be able to test 2,000 students at one time (at Central)."
Waters said his goal has been not just to add computer labs but to upgrade the technology in as many classrooms as possible.
"As each building gets renovated, we're adding a lab or two in each," he said. "We can't give up too many classrooms to computer labs, but we can make classrooms capable of becoming computer labs."
Van Hoozer said that the district's elementary schools also will each have two dedicated computer labs when construction is complete and that Lee Middle School will have three computer labs as well as computer-capable classrooms.
Of the 11 campuses under the bond, construction is completed at two — Santa Rita and Holiman elementary schools.
In addition to Central, work is under way at Lee and at Crockett, Goliad, Reagan, Bradford, San Jacinto and Glenmore elementary schools.
The next campus to be completed will be San Jacinto, one of the district's oldest.
"This summer we're doing ceilings, painting and flooring," Van Hoozer said.
The two-story school also has a shiny new elevator and a wheelchair ramp up to an entrance, as did Reagan, which is more than 100 years old.
A major goal of the bond project has been to bring the schools in compliance with the federal Americans with Disabilities Act. Students and adults will no longer have to be carried from one floor to another or into the buildings. Restrooms have been upgraded to accommodate wheelchairs.
The renovations also include upgrades for student safety, such as fire sprinkler systems and alarms.
Another major goal has been to remove the portable classroom buildings that have sprung up over the years across the district to accommodate shifting enrollments.
Van Hoozer said the district, when possible, is selling the portables after new classroom additions are completed.
"We had a couple of them over at Holiman that Novice ISD bought from us," he said. "The two at Central, PaulAnn Baptist Church bought one, and the Cowboy Church bought one.
"We've had individuals buy them from us. One man has bought a couple. He has a hunting camp, and he's using them for his bunkhouses and kitchen areas."
He said most of the portables are set up to house two classrooms with restroom facilities and have sold from $1,200 to $3,500 each.
"They have to go to sealed bids, and it just depends on what someone bids," Van Hoozer said. "We're not going to get rich on them, but the ones that we've had to have demolished — either because they were falling apart or their location on a campus, you can't get a truck in to get them out — have been costing us $10,000. So really, if we sell one for $3,000, we make $13,000 off of the deal."
The final project to break ground will be construction of a new building at Lake View High School.
"Lake View, which will be started in September or October, will be finished before several of these others are because Lake View is pretty much cut and dried," Van Hoozer said.
"It's a stand-alone building. It should be fairly quick. It will have 11 rooms and two science labs. They'll be able to get rid of the science labs at the old Lincoln and the portables and still have one more classroom."
Van Hoozer said three general contractors have worked on the 11 projects. Lee Lewis is doing Central, Bradford and Lake View; Templeton is handling San Jacinto, Crockett and Lee; and Mid-Tex is doing Reagan, Goliad and Glenmore.
"For the overall scheme, we're still within our budget. We've done that at every project," Van Hoozer said.
Voters approved a $117 million bond in 2008 to pay for renovations on 11 San Angelo Independent School District campuses. A guaranteed maximum price has been set for each project through the bidding process but does not include such costs as architect and engineering fees and asbestos abatement. Lake View High School is the final project about to go for a guaranteed maximum price, with construction expected to start in the fall.
Completion dates are estimates except for the two already completed — Santa Rita Elementary School and Holiman Elementary School.
School GMP Completion date
Santa Rita $2,460,292 August 2010
Holiman $6,664,912 July 2011
Lee $10,946,452 December 2012;
Track & field May 2013
Goliad $8,227,964 August 2012
San Jacinto $5,785,707 December 2012
Central $39,415,364 August 2013
Crockett $7,672,417 July 2013
Glenmore $4,800,000 August 2013
Bradford $7,200,000 March 2014
Reagan $5,791,637 June 2013
Lake View $3,000,000 est. October 2013
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Whitney English takes a photo of her daughter, Danyelle, in front of the school before the first day of classes Monday at Prattville Kindergarten.
- Filed Under
Backpacks are stuffed full, buses are rolling and teachers are manning their posts. It's back-to-school time in the River Region, which began with the first day of classes in Elmore and Autauga counties on Monday.
Montgomery County public school students return Aug. 22.
Area superintendents said they're ready and excited to get started. With a new year comes new principals, new projects, new programs and sometimes just a new approach to the curriculum. So sharpen those pencils and grab a spiral notebook -- class is in session. ...


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HARVEY FIERSTEIN 2 Articles
Final Broadway Performance Of Hairspray To Raise Money For Broadway Cares
The long-running Broadway musical Hairspray is about to close its doors. To celebrate all of it's success, the producers of the hit show are auctioning off an awesome prize package
George Clooney Joins List of Outraged Citizens Against Prop 8
Ecorazzi has been keeping you up to speed on Proposition 8, it's outrageous passing, and the stars who have something to say about it. Drew Barrymore and Ellen Degeneres were


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Hottest Body on 'RuPaul's Drag Race'? You Be the Judge
Hope you're hungry, because catch of the day is Santino Rice.
While we were ogling RuPaul's hunky Pit Crew, bitchy RuPaul's Drag Race judge and former Project Runway contestant was posting shirtless selfies on Instagram that are burning up the blogosphere. How'd we not know this was going on behind that judges table next to Ru's pajama bottoms?
And just in case you're wondering... sometimes referred to as "bisexual" in the media, Santino once said in an interview, "You can just call me gay but I like men and I am attracted to beautiful women. I didn't like the negativity that was attached to being gay growing up so that is why I have problems with the label."
And now we can just label the 38-year-old fashion designer a hot piece of ass.
See another shirtless Santino selfie on the next page.


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Xbox Live Gold members get Netflix update
updated 01:20 pm EDT, Mon April 9, 2012
Netflix update brings Kinect controls, more
Microsoft and Netflix have delivered a new update for the Xbox 360 that brings new functions to the app, the former's Larry Hryb revealed. The revamped media streaming client includes the ability to skip forward an back through movies and shows with buttons. Users with Kinect can also perform this using their voice or by waving their hand.
Equally new is a Zoom feature that lets users get rid of the letterbox by enlarging content to fill the entire screen. The color contrast has been enhanced to provide better colors and darker blacks.
Users will now have the ability to sign on to their Netflix accounts from other Xbox consoles as well. Finally, Netflix members in Canada, Latin America, the UK, and Ireland get the newfound ability to share TV shows and movies through Facebook.
Access is limited to Xbox Live Gold members so far.


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Ohio State Scheduled to Play Host to Maryland in 2013 Big Ten/ACC Challenge
May 8, 2013
COLUMBUS, Ohio- The 15th annual Big Ten/ACC Challenge Presented by DICK'S Sporting Goods will feature Maryland at Ohio State Dec. 4 in Columbus. The ESPN family of networks will televise the 12 games of the two-day event (Dec. 3-4). Times and television will be determined later this summer.
Thad Matta, head coach of the Buckeyes, has a 5-4 record in the Big Ten/ACC Challenge and has won four of the last five games in the event.
"We are looking forward to having the University of Maryland on our campus this year in the Challenge," Matta said. "The game will give fans of both programs a glimpse at what the series will look like when the Terrapins join the Big Ten in 2014-15."
Ohio State advanced to the 2013 NCAA Elite Eight in Los Angeles. The Buckeyes finished the 2012-13 season with an overall record of 29-8, which included a 13-5 record in the Big Ten regular season race. Ohio State finished tied for second in the Big Ten. The Buckeyes then captured the 2013 Big Ten Tournament title in Chicago.
Matta has led the Buckeyes to five-consecutive trips to the NCAA tournament, four-consecutive appearances in the NCAA "Sweet 16," five Big Ten titles in the last eight years and four-consecutive appearances in the annual Big Ten postseason tournament title game, earning championships in 2010, 2011 and 2013.
The Buckeyes return eight scholarship letterwinners and four starters in 2013-14. Seniors Aaron Craft and Lenzelle Smith Jr.lead a veteran team that includes five juniors, a sophomore and a pair of incoming freshmen.
Craft was the Big Ten's 2012 Defensive Player of the Year. He made the all-defensive team and was first team All-Big Ten last year. Craft is Ohio State's all-time steals leader with 248. He is just 18 points away for 1,000 career points and is on pace to become Ohio State's all-time assist leader as well. He has earned First Team Academic All-America honors in each of the last two seasons and was named Capital One Academic All-America of the Year for 2013 in Division I men's basketball.
Season Tickets
2013-14 season tickets for new buyers are on sale now. For more information, contact the Ohio State athletics ticket sales department by calling 1-800-GOBUCKS (select option 2). Fans will be directed to a sales representative who can discuss seating options over the phone or schedule a time to tour the Jerome Schottenstein Center to pick out seats.
Buckeyes In The Challenge
The Buckeyes In Big Ten/ACC Challenge
Ohio State vs. Maryland
Last Time vs. Maryland
The Ohio State Maryland Series
(1) National Invitation Tournament
Buckeye and Terrapin Ties
2013 Big Ten/ACC Challenge Schedule (times and networks are to be determined)


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Josh Wachholz of Oshkosh chains a John Deere boom sprayer to his trailer March 31 at Wausau Sales Corp., south of Merrill. The sprayer was purchased at an auction held March 28 at Wausau Sales Corp.
- Filed Under
The Great Recession took its toll on many businesses in central Wisconsin.
But its effect on auction companies was a bit different.
Carl Theorin, owner of Wausau Sales Corp., which auctions things like farm machinery, construction equipment and lawn & garden items, said his business conducted more auctions during the recession, but because times were tough, certain things didn't sell as well. So there were more auctions but weaker prices. ...


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Event Name- OR - Select an option below
Located in Aliso Viejo, Time-Out Tavern & Night Club features an impressive 21 TV's (as well as a couple of huge screens) ensuring a view of every sporting event in play from anywhere in the room. Gurgling water walls and several pool tables add to the scenery. There's also a nice-sized selection of draft beers and a full bar; weekday happy hours feature $2.50 domestic draft beers and well drinks. Depending on the nights, Time Out features live bands comedy as well as DJs rocking hits from the '70s to the present.


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Defining interpersonal violence
For some helpful information, additional definitions and guidelines, visit NotAlone.gov. The following definitions should be helpful, but are not legal definitions of these terms.
Interpersonal violence encompasses the following:
- Relationship or dating violence
- Sexual assault
- Harassment
- Stalking
- Family violence
- Physical violence
- Emotional violence
- Bullying
- Cyber bullying/Online harassment
Some helpful terms that act as a role in interpersonal violence:
More information defining acts of interpersonal violence can be found by visiting the University's Policies and Procedures webpage and the University's Title IX webpage.
1. Relationship or dating violence
Dating violence is any act of violence committed by a person who is or has been in a social relationship of a romantic or intimate nature with the victim. The existence of such a relationship shall be determined based on the victim's statement and with consideration of the type and length of the relationship and the frequency of interaction between the persons involved in the relationship. Two (or more) people may be in a romantic or intimate relationship, regardless of whether the relationship is sexual in nature; however, neither a casual acquaintance nor ordinary fraternization between individuals in a business or social context shall constitute a romantic or intimate relationship.
This term is used when a pattern of controlling behavior of a partner is evidenced in a relationship. The abusive behavior can be incremental over time resulting in the abused partner being isolated from others or made to feel incompetent, ashamed or guilt-ridden. The abuse can be emotional, physical, sexual or any combination thereof. Victims are often unaware that they are in an abusive relationship. Leaving this kind of relationship is extremely difficult, often requiring counseling and a great deal of support.
For more information visit our Dating Violence page.
2. Sexual assault
Sexual Assault refers to physical sexual acts perpetrated against a person's will or where a person is incapable of giving consent (e.g., due to the student's age or use of drugs or alcohol, or because an intellectual or other disability prevents the student from having the capacity to give consent). A number of different acts fall into the category of sexual violence, including rape, sexual assault, sexual battery, sexual abuse, and sexual coercion. Sexual violence can be carried out by school employees, other students, or third parties. All such acts of sexual violence are forms of sex discrimination prohibited by Title IX. Taken from the United States Department of Education.
For more information visit our Sexual Assault page.
3. Harassment
Harassment is any form of unwanted and offensive behavior. This can include physical conduct or written or verbal derogatory or discriminatory statements. Harassment can interfere with an individual's employment, academic performance, university participation, or emotional state. It can create an intimidating, hostile, or offensive environment.
For more information visit our Harassment page.
4. Stalking
Stalking refers to intentionally engaging in a course of conduct, directed at a specific person, which is likely to causes a reasonable person to fear for his or her safety or the safety of others or cause that person to suffer substantial emotional damage. It may include, but are not limited to, take the form repeatedly following such person(s), repeatedly committing acts that alarm, cause fear, or seriously annoy such other person(s) and that serve no legitimate purpose, appearing at a person's home or place of business, repeatedly communicating by any means, including electronic means, with such person(s) in a manner likely to intimidate, annoy, or alarm him or her, such as making harassing phone calls, leaving written messages or objects or vandalizing a person's property. Any unwanted contact between two people that directly or indirectly communicates a threat or causes the victim to feel fear can be considered stalking.
For more information visit our Stalking page.
5. Family violence
Family Violence can include emotional , physical, and sexual violence by one family or household member on another. Family Violence effects everyone not just the victim. Children who grow up in violent homes greatly risk the possibility of emotional, behavioral and physical problems that last for a lifetime. Depression; anxiety; violence toward peers; suicide attempt; drug & alcohol abuse and running away from home are just some of the issues that stem from the violence in the home.
6. Physical violence
Physical abuse is contact of one person on another intended to cause unwanted feelings of physical pain, injury, or other physical suffering. Scratching, punching, biting, strangling or kicking are a few examples. Physical violence does not have to leave an external mark to be reported.
7. Emotional violence
Emotional violence is behavior which does not give mutual importance and respect to another person's feelings. It is often the most difficult to pinpoint or identify. Emotional violence includes the refusal to listen to, or denial of, another person's feelings, telling people what they do or do not feel, and ridiculing or shaming their feelings. It happens when one person believes they have a right to control or dominate another person.
8. Bullying
Bullying is aggressive behavior that involves unwanted, negative actions. Bullying is a pattern of behavior repeated over time and an imbalance of power or strength. Bullying can take on various forms such as: derogatory comments and bad names, social exclusion or isolation, lies and false rumors, and threatened or forced to do things you don't want to do.
For more information visit our Bullying page.
9. Cyber bullying/ Online harassment
Cyber bullying is using the Internet, mobile phone or other digital technologies to harm others. Cyber bullying can happen 24 hours a day, 7 days a week, and can reach a person even when he or she is alone. It can happen any time of the day or night. Cyber bullying messages and images can be posted anonymously and distributed quickly to a very wide audience; it can be very difficult to delete once it is posted.
10. Consent
The presence of consent involves explicit communication and mutual approval for the act in which the parties are/were involved. Consent is clear, knowing and voluntary. Silence, in and of itself, cannot be interpreted as consent. A sexual encounter is considered consensual when individuals willingly, knowingly, and mutually engage in sexual activity.
Consent MUST BE: informed, voluntary, freely and actively given, person had the right to change his/her mind at ANY time.
Consent is NOT: assumed, based on body language, dating does not mean there is consent to have sex, consent for one act does not mean consent for all sexual acts, obtained by use of physical force, compelling threats, intimidating behavior or coercion, decided when under the influence of alcohol or substances.
According to universal SUNY policy and the Violence Against Women Act, In summary, consent is:
- Consent is a voluntary agreement to engage in sexual activity;
- Someone who is incapacitated cannot consent;
- Past consent does not imply future consent; silence or an absence of resistance does not imply consent;
- Consent to engage in sexual activity with one person does not imply consent to engage in sexual activity with another;
- Consent can be withdrawn at any time; and
- Coercion, force, or threat of either invalidates consent.
11. Role of alcohol and other substances
The use of alcohol and other drugs can have unintended consequences for both parties involved. Alcohol and other drugs can create an atmosphere of confusion over whether consent is freely and affirmatively given. The use of alcohol and other drugs never makes someone at fault for being sexually assaulted. When both parties are under the influence of alcohol or other substances or is intoxicated, the individual who initiated sexual contact is identified as the aggressor. The use of alcohol or other drugs will never function as a defense for any behavior that violates a person's rights.
Report crimes of interpersonal violence to the University Police; also visit our Resources page for more information.


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Congratulations to the GPB Downton Abbey Contest Grand Prize Winner, Jim Belcher! His win concludes the Downton Abbey contest; thank you so much to everyone who entered and congratulations to everyone who won.
Let's hope the wait for Season Three isn't too long!
All volunteers receive training, free parking and a catered meal provided by C. Parks Catering.Get More Info »