Proteus mirabilis, which is a pathogen that forms biofilms in vivo, can swarm over hard surfaces and form a variety of spatial patterns in colonies. Colony formation involves two distinct cell types: swarmer cells that dominate near the surface and the leading edge, and swimmer cells that prefer a less viscous medium, but the mechanisms underlying pattern formation are not understood. New experimental investigations reported here show that swimmer cells in the center of the colony stream inward toward the inoculation site and in the process form many complex patterns, including radial and spiral streams, in addition to previously-reported concentric rings. These new observations suggest that swimmers are motile and that indirect interactions between them are essential in the pattern formation. To explain these observations we develop a hybrid model comprising cell-based and continuum components that incorporates a chemotactic response of swimmers to a chemical they produce. The model predicts that formation of radial streams can be explained as the modulation of the local attractant concentration by the cells, and that the chirality of the spiral streams results from a swimming bias of the cells near the surface of the substrate. The spatial patterns generated from the model are in qualitative agreement with the experimental observations.The enteric bacterium  Proteus mirabilis is an enteric bacterium that forms biofilms on urinary catheters, but in laboratory experiments it can swarm over hard surfaces and form a variety of spatial patterns. Understanding these patterns is a first step toward understanding biofilm formation, and here we describe new experimental results and mathematical models of pattern formation in Proteus. The experiments show that swimmer cells in the center of the colony stream inward toward the inoculation site and in the process form many complex patterns, including radial and spiral streams, in addition to concentric rings. To explain these observations we develop a model that incorporates a chemotactic response of swimmers to a chemical they produce. The model predicts that formation of radial streams can be explained as the modulation of the local attractant concentration by the cells, and that the chirality of the spiral streams can be predicted by incorporating a swimming bias of the cells near the surface of the substrate.Bacteria frequently colonize surfaces and grow as biofilm communities embedded in a gel-like polysaccharide matrix, and when this occurs on catheters, heart valves and other medical implants, it can lead to serious, hard-to-treat infections.  Escherichia coli cells grow, divide, and self-organize into patterns ranging from outward-moving rings of high cell density to chevron patterns, depending on the initial concentration of the nutrient Salmonella typhimurium, a closely-related species, can also form concentric rings and other complex patterns in similar conditions Bacillus subtilis forms patterns ranging from highly branched fractal-like patterns to compact forms, depending on the agar and nutrient concentrations A variety of spatial patterns in growing bacterial colonies are found both in nature and in the lab Proteus mirabilis is an enteric gram-negative bacterium that causes urinary tract infections, kidney stones and other diseases Proteus was described over 100 years ago P. mirabilis is a vegetative swimmer cell that is 1–2 E. coliProteus forms spectacular patterns of concentric rings or spirals. Swimmers differentiate into highly motile, hyperflagellated, multi-nucleated, non-chemotactic swarmer cells that may be as long as 50–100 P. mirabilis.When grown on hard agar Proteus colonies has been interpreted as a result of periodic changes in the velocity of the colony's front, caused by the cyclic process of differentiation and de-differentiation of swimmers into swarmers  what induces the inward movement of swimmer cells, (2) why do they move in streams, (3) why do radial streams quickly evolve into spiral streams, and (4) quite surprisingly, why do all the spirals wind counterclockwise (CCW) when viewed from above. To address these questions we developed a hybrid model comprised of a cell-based component for cell dynamics and a continuum component for nutrients and the chemoattractant secreted by swimmer cells. The model has provided biologically-based answers to the questions above and guided new experiments. Previous models, including a continuum chemotaxis model for patterning we developed earlier P. mirabilis culture is inoculated on a hard agar-like surface containing rich nutrient, the colony grows and expands. Under the conditions used here, the colony front expands continuously  underlying the formation of radial and spiral streams, rings and trains by swimmers, and what determines the chirality of the spiral streams. The macroscopic patterns are very different and more dynamic than the patterns formed in The spatial patterns of interest here are formed in the center of the colony where cells are primarily swimmers, while the role of swarmers is mainly to advance the front and to affect the swimmer population by differentiation and de-differentiation. Thus we first focus on modeling the dynamics in the patterning zone in the colony center , and latP. mirabilis is very similar to that of E. coliE. coli have been found in the Proteus genome P. mirabilis and E. coli, we describe motility and signal transduction in the former using the key ideas from the latter.It has been known for many years that the chemotaxis signal transduction pathway in E. coli cells swim using a run-and-tumble strategy, which consists of more-or-less straight runs punctuated by random turns. In the absence of an attractant gradient the result is an unbiased random walk, with mean run time Each swimmer cell  is solved on a square domain using the ADI method with no-flux boundary conditions, while cells move off-grid. For each time step E. coli as well Before the emergence of radial streams, the colony expands with a continuous moving front  due to tE. coli . This has also been found both theoretically and experimentally in coli see . If we dcoli see . NumericIn the presence of a macroscopic gradient a similar analysis, taken along a 1D circular cross-section of the 2D aggregation field, predicts the breakup of the uniform distribution, but in this situation the 2D pattern of local aggregations is aligned in the direction of the macroscopic gradient. This is demonstrated in a numerical experiment in which cells are placed on a cylindrical surface with constant attractant gradient . Thus thE. coli in bulk solution and near surfaces. When far from the boundary of a container, E. coli executes the standard run and tumble sequence, with more or less straight runs interrupted by a tumbling phase in which a new, essentially random direction is chosen.  Resistive force theory has been used to derive quantitative approximations for the radius of curvature as a function of the distance of the cell from the surface and other cell-level dimensions, treating the cell body as a sphere and the flagellar bundle as a single rigid helix Since the cells are small the Reynolds number based on the cell length is very small . Each amino acid was used in concentrations varying from 0.25 mM to 7.5 mM in both thicknesses of agar. The plates were point inoculated and placed in a humid chamber at room temperature for at least 20 hrs. Bacteria growing on 10 and 20 ml plates with 0.00l M of Aspartate, Methionine and Serine formed dense moving outer ring which we interpret as a chemotactic ring. Bacteria grown on all remaining amino acids produced colonies with the higher density at the point of inoculation and homogeneous cell distribution in the rest of the colony.In the implementation of the cell-based model, cell motion is simulated by a standard Monte Carlo method in the whole domain, while the equations for extracellular chemicals are solved by an alternating direction method on a set of rectangular grid points. In this appendix, we present the numerical algorithm in a two-dimensional domain with only one chemical - the attractant - involved. Each cell is described by its position e method . We denoSince two components of the model live in different spaces, two interpolating operators are needed in the algorithm. ractions . On the We consider here a periodic boundary condition. The detailed computing procedure is summarized as follows.S1. Initialization.Initialize the chemical fields.Initialize the list of swimmer cells. Each cell is put in the domain with random position, moving direction and age. S2. For time step l Click here for additional data file.Figure S2Simulated streams on a 2-D cylindrical surface. When there is no swimming bias, the alignment of the streams are parallel to the initial attractant gradient. This is demonstrated in the computation where cells are put in a cylindrical surface with constant attractant gradient. The cell density profile is in units of (EPS)Click here for additional data file.Video S1Time evolution of radial and spiral streams. The real time is shown in the movie. Compressed using Microsoft Video Movie Maker.(WMV)Click here for additional data file.


Pseudomonas fluorescens strains. CLP production is known to be regulated at least by the GacA/GacS two-component pathway, but the full regulatory network is yet largely unknown. In the clinical strain MFN1032, CLP production is abolished by a mutation in the phospholipase C gene (P. fluorescens to be explained.Cyclolipopeptides (CLPs) are biosurfactants produced by numerous  Pseudomonas fluorescens are ubiquitous bacteria endowed with a capacity to adapt to many environments, namely by producing a wide range of extracellular molecules such as enzymes, toxins, antibiotics and biosurfactants. In these species, the main characterized biosurfactants are cyclolipopeptides (CLPs). They are involved in swarming motility and, depending on the strain and/or on the nature the considered CLPs, are sometimes required for biofilm formation Pseudomonas species, whereas others seem to be species dependent or even strain dependent. The global regulatory system GacS/GacA controls CLP production at a post-transcriptional level by the Rsm pathway in all Pseudomonas spp. P. fluorescens, the requirement of the N-acylhomoserine lactone mediated quorum sensing for CLP production has only been demonstrated in a few strains P. fluorescens SS101 and SBW25 (strains that do not produce N-acylhomoserine lactone), the LuxR-type transcriptional regulator positively regulates the production of CLPs. These LuxR-type regulators do not harbour the autoinducer-binding domain found in most quorum sensing associated LuxR regulators. Lux R-type genes are under the control of both GacS/GacA, and of the serine protease ClpP in a GacS/GacA-independent way Up to now studies have mainly focused on the effects of environmental conditions on CLP production , but data concerning transduction of the signals are quite limited P. fluorescens clinical strain MFN1032 displays hemolytic activity due both to phospholipase C (PlcC) and CLPs. A knock out mutation in gene In a previous study Pseudomonas aeruginosa is subjected to an epigenetic switch between a non-inducible and an inducible state. The positive feedback is due to the self-regulating gene exsA, a general positive regulator of the regulon. More recently, MacLeane and Studholme Pseudomoans syringae, displaying a bistability under the control of the GacA/GacS node.Heterogeneity within a bacterial population is a well-known phenomenon, which supposedly allow bacteria to invade a wide range of ecosystems and increases the overall fitness of the species. The heterogeneity could result from genetic rearrangement (high rate mutations or inversions of a DNA segment), or DNA methylation, but also to epigenetic switches Here we used a Boolean approach to construct all the minimal regulatory networks of CLP production, consistent with the observations previously reported. We show that the simplest explanation for these behaviours is an epigenetic switch of the production of CLPs, the pivotal self regulating gene being unknown.Boolean network with A asynchronous state graph of As argued by Thomas, the appearance or disappearance of a protein occurs after a vacillating delay stable state of the network. More generally, an attractor is a smallest non-empty subset of states that we cannot leave by following the paths of the state graph (stable states are attractors of size one). If we assume that, at each time If interaction graph of The We denote by In the next section, we are interested in the set of all the minimal Boolean networks whose asynchronous state graph satisfies some properties extracted from biological observations. To compute these networks, we used SMBioNet software P. fluorescens clinical strain MFN1032. This strain displayed hemolytic activity (HA) and PlcC and CLPs (which we previously showed were necessary for hemolytic activity). A mutation in How can we explain this surprising, but reproducible, process? The aim of this section is to propose a partial answer by exhibiting Boolean models that “explain” the mechanism underlying this process by the presence of genetic regulatory systems displaying two attractors, which describe an epigenetic switch. For that, we proceeded in two steps. First, we interpreted the previous observations in terms of Boolean networks, and then, we exhibited Boolean networks that were consistent with this interpretation.For the interpretation, we used the following hypotheses. (1) The production of CLPs in strain MFN1032 is controlled by an asynchronous Boolean network To be consistent with this interpretation of the results, The asynchronous state graph of  contains an attractor  such that: (1)  and  for every state  in  (MFN1032); (2) the asynchronous state graph of  contains a path from  to an attractor  such that  for every state  in  (MFN1037); and (3) the asynchronous state graph of  contains a path from  to an attractor  such that  and  for every state  in  (MFN1038).Now, we must determine whether Boolean networks exist which satisfy property Using intensive computation, we have generated the There are two minimal consistent Boolean networks with respect to the number of interactions. These two networks contain three interactions, and are shown in Network 2 could be discussed similarly. Since PlcC is absent in the early growth phase and is not sufficient to restore In a previous study, we have shown that strain MFN1032 displays phenotypic variations when incubated in specific conditions. The results are also summarized in Pseudomonas spp.) and generate group 1 variants, where the WT phenotype is restored by complementation by one of the two genes encoding the Gac system. A second class of variants, group 2, is composed of variants, which are not restored to WT by complementation by the Frequently, For the interpretation of group 1 variants, we consider a network As previously demonstrated, the WT phenotype is interpreted by the presence, in the asynchronous state graph of To be consistent with both this interpretation of the The asynchronous state graph of  contains an attractor  verifying points (1–3) of property , and two additional points: (4) the asynchronous state graph of  contains a path from  to an attractors  such that  and  for all states  in  (Group 1); (5) the asynchronous state graph of  contains a path from  to an attractor  such that  and  for all states  in  (complementation of  gene in Group 1).We now exhibit Boolean networks satisfying property Using intensive computation, as previously done, we have generated, among the among the Surprisingly, each of the 2400 consistent Boolean networks is in agreement with this hypothesis. Indeed, for each consistent Boolean network, once a The simplest biological regulatory network (with a negative interaction) deduced from the model that accounts for all observations is shown in From a biological standpoint, this approach suggests at least three experiments to validate the model with a negative According to the dynamics of Pseudomonas fluorescens strain Pf-5, a CLP producer Secondly, a pulse of R in the wild type strain could lead to group 2 variants. In literature, no negative regulator for CLP production has yet been described. Indeed, identification of such regulators is difficult with the routinely used random mutagenesis. The CLP phenotype of an And last, without other valid data from literature, random mutagenesis on From a biological point of view, the Boolean approach has proven particularly well suited for this study for several reasons: (i) the qualitative aspect of the observations, which are expressed in terms of the presence/absence of CLPs and PlcC; (ii) the lack of information about the genetic network controlling CLP production; (iii) reproducible but not easily nor understood straightforward observations.The particularity of our modelling study consists in translating the observations in a formal way, and in computing all the Boolean networks which satisfy the property resulting from this translation, without any assumption on the topology of the considered network . By considering only the minimal Boolean networks  consistent with the observations, we are able to propose new hypotheses concerning the regulatory network of CLP production. There is a strong probability that a yet unknown regulator, endowed with positive self-regulation is negatively controlled by PlcC and negatively controls the production of CLPs.Pseudomonas strains, in which numerous non-CLP producer strains and CLP producers are found in the same environment By contrast, the hypothesis that type 2 variants are due to a mutation/reversion in one of the Figure S1The 12 Boolean networks  with three components  that are consistent with property  and with an interaction graph in which  has no outgoing interaction. The graphical conventions used to described the interaction graph of each network are as follows: arrows of form (EPS)Click here for additional data file.


The analysis of risk for the population residing and/or working in contaminated areas raises the topic of commuting. In fact, especially in contaminated areas, commuting groups are likely to be subject to lower exposure than residents. Only very recently environmental epidemiology has started considering the role of commuting as a differential source of exposure in contaminated areas. In order to improve the categorization of groups, this paper applies a gravitational model to the analysis of residential risk for workers in the Gela petrochemical complex, which began life in the early 60s in the municipality of Gela  and is the main source of industrial pollution in the local area.A logistic regression model is implemented to measure the capacity of Gela "central location" to attract commuting flows from other sites. Drawing from gravity models, the proposed methodology: a) defines the probability of finding commuters from municipalities outside Gela as a function of the origin's "economic mass" and of its distance from each destination; b) establishes "commuting thresholds" relative to the origin's mass. The analysis includes 367 out of the 390 Sicilian municipalities. Results are applied to define "commuters" and "residents" within the cohort of petrochemical workers. The study population is composed of 5,627 workers. Different categories of residence in Gela are compared calculating Mortality Rate Ratios for lung cancer through a Poisson regression model, controlling for age and calendar period. The mobility model correctly classifies almost 90% of observations. Its application to the mortality analysis confirms a major risk for lung cancer associated with residence in Gela.Commuting is a critical aspect of the health-environment relationship in contaminated areas. The proposed methodology can be replicated to different contexts when residential information is lacking or unreliable; however, a careful consideration of the territorial characteristics  is suggested when specifying the area of application for the mobility analysis. Epidemiological studies have extensively considered mobility, intended as the change of individual residence, as a risk factor for health. Mobility accounts for accessibility to health services -3, and iFrom a methodological perspective, Rogerson and Han  argue thHowever, mobility implies not only that people change their residence, but also that  they commute on a daily basis, travelling from their residence to a "distant" workplace. From this perspective, commuting has been investigated as a factor that influences individuals' exposure during travel time -26, as aCommuting is, then, an important topic in environmental epidemiology and may help to shed light on residential/occupational health risks for different groups. Nevertheless, even though commuting has been intensively studied from geographic  and With the aim of integrating geo-economic quantitative methodologies with epidemiological studies, this study offers a multidisciplinary perspective in order to improve the definition of groups of exposed populations in cases in which the reconstruction of individuals' residential history is not possible (either due to missing or unreliable information).Drawing from mobility gravity models, the paper proposes a quantitative method based on the use of a logistic probability model, to define a possible valuable classification of a population of petrochemical workers into commuters and residents categories; on these grounds, we then test residential risk for lung cancer within a cohort of workers from the Gela petrochemical complex . More generally, the application of commuting analysis may be important for epidemiological investigations, and particularly for occupational epidemiology.In Italy, the region of Sicily (which is the biggest island in the Mediterranean) contains three areas that have been declared "at high risk of environmental crisis" ("risk areas"), located in three different portions of the territory, as shown in Figure Referring to the specific Italian legislation, "risk areas" include territories where the presence of large industrial plants has an important impact on the environment and may harm human health. The general criteria for the determination of the perimeters of risk areas are open to debate and must always be scrutinised. The formal recognition by law of the condition of risk in a particular area, follows specific risk assessment procedures. Sometimes risk areas are identified after the occurrence of particular events raising environmental concern, while in other cases, the recognition of environmental and health risk comes after a long "invisible" process of contamination or when significant epidemiological factors single out a population group living in a particular area .In this study, we specifically concentrate on the site of Gela, a town of 77,000 inhabitants, located on the south-west coast of Sicily and characterised by relative isolation with respect to adjacent municipalities. The town underwent great changes in only a few years after 1956, when oil fields were discovered in its vicinity, both onshore and offshore; since the early 1960s, Gela has hosted a large oil refinery, together with a number of important chemical and petrochemical industries. The industrial area extends along a large portion of the territory in comparison to the size of the urban area.In 1990, an extended territory comprising the municipalities of Gela, Butera and Niscemi  due to heavy chemical soil pollution derived from the petrochemical complex.2, PM10, NO2, O3 and benzene [Several studies report information about environmental contamination levels in the area of Gela; in particular, two specific studies on pine needles and road dust samples showed that the entire area of Gela is heavily affected by industrial and urban emissions of metals and metalloids ,48; addi benzene , while,  benzene . Some ofMore generally, evidence of a risk of lung cancer, associated with residence near petrochemical plants has been suggested by several studies. A higher risk of lung cancer was observed in people residing in the most polluted areas of Teesside in the UK ,52 and iUsually, the contribution of the epidemiological investigation of occupational cohorts is related to the occupational risk evaluated in the production setting under study .In the industrial site of Gela, the large petrochemical complex is the main source of environmental pollution. Some small-area mortality studies of the Gela resident population showed an excessive risk of lung cancer among men and women -59, showMore recent studies have shown that commuting may influence the result of small-area studies and should be carefully considered in the identification of the control population. Selecting areas with similar socio-economic characteristics and with no (or low) commuting to Gela, obtains higher Standardized Mortality Ratios than using neighbouring municipalities .In this frame, the analysis of workers' mortality and/or morbidity profiles can help to elucidate the environmental/residential risk, thus contributing to the description of the local epidemiological context. In fact, a more intense exposure should be assumed for workers residing within the contaminated area compared with commuters, giving rise to the expectation of a higher lung cancer mortality-rate among resident workers.In general , information from employment rosters may neither be used to reconstruct residential history, nor to define residence at the moment of enrolment. The latter in particular is true for several reasons: a) workers may be hired before the official change of residence takes place ; b) electoral legislation encourages poll participation by subsidizing travel for people living away from their official place of residence; c) many people may have a strong preference to maintain residence in their birthplace in order to have closer contact with their original family.In the case of the Gela petrochemical complex, for instance, the employment rosters show that there are workers officially residing at a great distance from Gela, and that Gela's poor communication infrastructures  make it impossible for commuters to reach their workplace, even if they reside in the same region. As a result, residence information from the employment rosters is an unreliable criterion for a qualitative classification of workers as commuters vs. residents, while the simple use of place of birth as a classification criterion, overestimates the number of commuters. Alternative methodologies need to be developed.Evidence about commuting among workers was initially inferred from several documents and successively confirmed by a qualitative sociological study .Pasetto et al.  analyzedIn what follows, a methodology based on the application of mobility models is developed, in order to obtain a more accurate classification criterion to separate "commuting" and "resident" workers, and it is applied to the Gela petrochemical workers' cohort.Mobility is a kind of spatial interaction whose analysis generally relies upon the application of gravity-type schemes ,66 that Tij is the flow of "interactions" between locations i and j, A(i) and B(j) are unspecified origin and destination weight functions, which may contain centre attributes relative to its economic mass, and F(dij) is defined as a distance deterrence (or distance-decay) function, which accounts for the effect of distance d on T. The specification and combination of origin and destination functions may vary depending on the assumptions made about model parameters and variables. For an in-depth review of the theoretical aspects of gravity models, see Fotheringham and O'Kelly [where  O'Kelly .Gravity models and distance-decay functions have been applied to a wide range of research fields, from the analysis of social phenomena ,70 to biAs far as the distance-decay function specification is concerned, both the measure of spatial separation and the specific functional form of the relation have been debated ,81. For β measures the effect of distance friction. Structural properties of the exponential function make it appropriate to model short distance interactions (intra-urban mobility), while power specification is more suitable for longer distance interactions such as migration flows [where the parameter on flows .Within an unconstrained setting, the complete model can be structured as follows for power or exponential decay functions, respectively:From an empirical point of view, a widely used approach to investigate spatial interaction, is to calibrate the model using log-linear regression ,68; alteOur aim in implementing the mobility analysis, is to derive a methodological device that can be used to classify workers into "residents"/"commuters" categories in case the only reliable information is relative to the individuals' birthplace. To this purpose, a gravity-type model is implemented to estimate the probability for a "central locality", where a specific plant is established, to attract commuting flows from other distant places. Probability of commuting will then become the criterion to discriminate observations in the cohort study, according to the workers' place of birth. Working on census data, we need to obtain probabilities from count values, so that a logistic regression that accounts for the origin's economic mass and distance from destination is the most appropriate functional form for this kind of application of gravity-type models.In our case, we are firstly interested in elucidating to what extent Gela increases commuting flows from "distant" localities in order to identify a critical distance (the "commuting threshold"), discriminating petrochemical workers according to their birthplace. In fact, assuming that Gela-born people employed at the petrochemical complex reside in Gela, workers born outside this municipality may have either moved their residence to Gela, or maintained their residence in a different site, regularly commuting to Gela. Having identified the commuting threshold, workers born outside that distance will be considered "moved to Gela", while individuals born within this area will be classified as "commuters".B(j) component of model (1) disappears and mobility can be estimated as an unconstrained function of the origins' economic mass (A(i)) and distance from Gela (dij).Clearly, in the presence of a single destination, its characteristics are invariant in the model: the Hence, having transformed Italian Statistics Bureau Census count data on inter-municipal commuting  into a dThe estimated model is then:i pand 1 - i pare respectively the probability of observing a positive and a null flow of commuters to Gela. According to the gravitational pattern, explanatory variables are, distance in kilometres (dist) of each municipality from Gela and a proxy for the origins' "economic mass", provided by labour force (lf); the latter is treated as a dummy variable on the basis of classification into quartiles , while a one-way journey by train takes from 7 h38 m to 11 h41 m . As a consequence, we have restricted the analysis to 367 Sicilian municipalities less than 248 km from Gela.In order to limit the extension of our geographic analysis and to define the observations to be considered, we notice that the furthest locality from Gela where a positive commuting is found, is Trapani, at a distance of 248 km.; further, to reach Gela by car from the Italian peninsula, one has to cover a distance of approximately 500 km. at a cost of nearly 100 € per return journey, spending more than 7 hours  show a good fit of the estimated probabilities with respect to the empirical ones. The individual significance of coefficients, as measured by the Wald test, is very high, confirming the reliability of the estimated model. Moreover, the signs of coefficients are coherent with the theoretical background.As illustrated in Table On the basis of the conventional probability cut-off of 0.5, we assume that no commuting originates from municipalities with a probability value lower than or equal to 0.5, so that, for each "economic mass" category, a threshold distance for commuting can be fixed in correspondence to the 0.5 estimated probability. The model produces four "distance thresholds" relative to the different economic mass consistency of the origin municipalities; these thresholds, as reported in Table In accordance with the assumptions of the gravitational model, a greater dimension of the origin municipalities implies higher distance thresholds.By comparing estimated and observed values, the model correctly classifies nearly 90% of observations  Moved to Gelawhen hired: workers born in Sicilian municipalities with the probability of commuting defined by the model as <0.5b) Commuters: workers born in Sicilian municipalities with the probability of commuting defined by the model as ≥ 0.5c) The study population included 5,627 workers born in Sicily and employed in the petrochemical complex from 1960 -- the year plant operations started -- to 1993. The vital status follow-up was from 1960 to 2002.Mortality Rate Ratios (RRs) for all causes, all neoplasms and lung cancer, were estimated comparing workers by residence category. A Poisson regression model, controlling the RR for age and calendar period was applied using STATA 11.0 software; Confidence Intervals, CI (90%) were estimated by the maximum likelihood method. A regression model was also performed adding the variable of job title (results not reported); RR estimates did not significantly change (less than 8% for lung cancer) in the sensitivity analysis made by attributing different job categories to the subjects without information on job title.Descriptive data on workers by residence category are reported in Table commuters as a reference, the RR for lung cancer is 1.71 (0.92-3.17) for workers classified as moved to Gela, and 1.7 (1.03-2.81) for workers born in Gela; results are reported in Table Comparing mortality by place of birth and using The results obtained by applying the proposed categorization of residence are coherent with our hypothesis on residential risk for lung cancer mortality: a major risk is associated with residence in Gela.RR results could be partly attributed to differences in distribution of other risk factors for lung cancer between residential categories, such as differences in smoking habits, which is the main recognized risk factor for lung cancer . Though,commuters have a lower residential/environmental risk of mortality from lung cancer compared with workers who were likely to have been residents in Gela.Despite some limitations, the results support the hypothesis that In this paper a multiple logistic regression model has been implemented for the estimation of distance thresholds to be applied in order to classify Gela's petrochemical workers in the following categories: "commuters", "moved to" and "residents". As in many retrospective studies, information from employment rosters about workers' place of residence are not reliable and reconstruction of residential history is not possible.In similar situations, we suggest classifying population according to birthplace information, implementing the following procedure: a) using external data on workers' mobility , construct a dichotomous variable for municipalities according to the presence of workers commuting to the destination under study , attributing value 1 in the case of positive mobility and value 0 in the case of no commuters; b) classify municipalities according to the dimension of their labour force, grouping count data into quartiles in order to consider the role of "economic mass" of localities; c) implement a logistic regression model to estimate a "probability of commuting" as a function both of distance and of four dummies accounting for the "economic mass" of the origin municipality; d) define "commuting origins" all municipalities where the probability of commuting is equal to or higher than 0.5 and, consequently, establish the "commuting threshold" at the distance that corresponds to a probability of 0.5 for each dimensional group of municipalities; e) classify workers that were born outside the commuting threshold as "moved to", workers that were born within the threshold as "commuters", and workers that were born in the destination municipality as "residents"; f) analyze data according to the resulting classification.As far as the mobility analysis is concerned, the study is subject to implicit assumptions and restrictions:1) The cohort study regards a specific group of workers , while mobility analysis is conducted on the labour force as a whole. This implies that petrochemical workers have the same commuting behaviour as the total Gela labour force.2) The cohort study refers to the population that had been hired at the petrochemical complex during the 1960-1993 period, while the mobility analysis was based upon 2001 census observations. This implicitly assumes that the commuting habits of the Gela labour force  remained constant over the period 1960-2001.3) Mobility analysis does not account for differences in accessibility conditions between the origin municipalities. Further developments should consider the distinction between different road characteristics  and control for other modal conditions (railways).The definition of residential categories obtained from the analysis of the observed mobility patterns, reduces misclassification of residential status for a qualitative categorisation, in the absence of the individual data necessary to correctly define a residential history for each subject. Further research should reveal more about the impact of commuting on exposure to environmental risk factors for populations living/working within contaminated areas.Finally, as no ad hoc assumption is required, the methodology can be replicated to different contexts. Verification of mobility phenomena using qualitative sociological studies is suggested. Furthermore, a careful consideration of the specific characteristics of the regional context  is advised when specifying the area of application for the mobility analysis.The authors declare that they have no competing interests.GS collaborated on the development of the idea for the study, on the definition of the mobility model supervising the research; RPo undertook the mortality analysis providing the workers' cohort data and the results section; EG worked on data acquisition and contributed to the mobility analysis providing the commuting probability sub-section; MM performed the statistical analysis for specifying commuting probabilities and prepared the mobility model results sub-section; MLR provided feedback on commuting study design and interpretation of results. PM cooperated to the background analysis as far as the study area is concerned, providing figures and maps. All authors read and approved the final manuscript.


One of the most common goals in this field is the generation of a high rate chemical producing strain. A major hurdle with this approach is that many chemicals do not have easy to recognize attributes, making their screening expensive and time consuming. To address this problem, it was previously suggested to use microbial biosensors to facilitate the detection and quantification of chemicals of interest. Here, we present novel computational methods to: (i) rationally design microbial biosensors for chemicals of interest based on substrate auxotrophy that would enable their high-throughput screening; (ii) predict engineering strategies for coupling the synthesis of a chemical of interest with the production of a proxy metabolite for which high-throughput screening is possible via a designed bio-sensor. The biosensor design method is validated based on known genetic modifications in an array of E. coli strains auxotrophic to various amino-acids. Predicted chemical production rates achievable via the biosensor-based approach are shown to potentially improve upon those predicted by current rational strain design approaches. (A Matlab implementation of the biosensor design method is available via  A rational design approach - focused on the engineering of cellular phenotypes using rational modifications  based on existing stoichiometric, kinetic, and regulatory knowledge of a system A combinatorial approach - generating genetic diversity in a population followed by screening and selection for improved phenotypes inverse metabolic engineering (IME), which aims to discover the genetic factors that confer the phenotype and transfer them to another strain by directly applying these genetic modifications In recent years, metabolic engineering has emerged as a discipline that utilizes modern genetic tools for the construction of organisms capable of fuel and chemical production. Metabolically engineered microbial strains are now being used in the industry for the production of various chemicals Computational modelling in metabolic engineering has traditionally been used to rationally design the effect of genetic modifications on metabolism. However, such modeling approaches commonly involve either kinetic analysis E. coliThe combinatorial approach for metabolic engineering via random mutagenesis followed by screening for specific phenotypes of interest, has long been the gold standards for strain improvement in industry. A variety of recombinant DNA techniques are available for generating random genetic changes, thus introducing the possibility of uncovering regulatory, kinetic, or unknown/poorly understood targets not encompassed in current models  design microbial biosensors for chemicals of interest based on substrate auxotrophy  that canC, and a definition of a growth medium denoted by M, the biosensor design method aims to search for genetic modifications such that: (i) The bio-sensor strain would grow in a medium that consists of at least nutrients that are in M and C, and (ii) would not grow in a medium where C is absent, even if it consists of all metabolites (other than C) that can be transported into the biosensor strain. Notably, the common definition of substrate-auxotrophy is less restrictive than the above, and in many cases, strains considered auxotrophic for a chemical C, may actually also grow in the absence of C, utilizing a different substrate as input to synthesize C. We hence refer to a microbial strain that realizes the above growth constraints as being ultra-auxotrophic for chemical C. A microbial strain that is ultra-auxotrophic for C (considering some medium M), can be used as a biosensor within combinatorial metabolic engineering experiment, to detect and quantify the concentration of C , with the total biomass of the grown biosensor strain reflecting the concentration of C (as further explained below). The requirement for ultra-auxotrophy guarantees that the biosensor strain would not grow in case C is absent from the spent media, regardless of which additional chemicals were potentially secreted by the producer strains.Given a metabolic network model for some microbial species, a chemical to be sensed denoted by The search for a set of gene knockouts that would give rise to ultra-auxotrophy is performed via a bi-level optimization problem, considering stoichiometric mass-balance, reaction directionality, and knockout constraints . The latter medium, in which a large number of nutrients are expected to be manually added to the spent media is more complex from an experimental perspective, though as shown below, it increases the number of designed biosensors and enables to better quantify the concentration of sensed chemicals. We restricted the analysis to allowing up to a total of three knockouts. When considering a minimal medium, we predict biosensor designs for 43 chemicals, and when considering a rich medium, we predict additional biosensor designs for 10 chemicals  shows a good match between the two (E. coli should be able to utilize indole as a substrate to produce tryptophan (Comparing the predicted amino-acids biosensors with a list of known amino-acid auxotrophic strains (extracted from the Coli Genetic Stock Center (CGSC);  the two . Specifi the two . Our anayptophan . NotablyE. coli). Hence, in this case, the concentration of the sensed chemical can be accurately determined based on the total biomass of the grown biosensor strain. When only glucose minimal medium is assumed to be added to the spent media, the biosensor's biomass yield may change depending on the secretion of additional chemicals by the producer strain. For example, the xylose biosensor achieves a significantly higher biomass yield when additional metabolites (other than xylose) not included in glucose minimal media are present in the media . FBA is applied to predict the maximal theoretical production yield of a chemical of interest, while enforcing a minimal growth rate of 0.1 mmol/gr(DW)h to maintain viability . The results show that combinatorial metabolic engineering experiments aiming to over-produce chemicals using the predicted biosensors would enable to produce 25 metabolites with a rate greater than zero . RobustKnock is a robust variant of OptKnock that searches for knockout combinations that maximizes the minimal  secretion rate of the chemical, considering the presence of the alternative pathways in a metabolic network that may prevent the organism from reaching the maximal theoretical chemical production rate predicted by OptKnock  by coupling their production with biomass formation. Furthermore, the maximal possible production yields predicted by OptKnock and RobustKnock for these chemicals are significantly lower than the optimal yields that may theoretically be achieved by the biosensor-based approach , testifyE. coli under glucose minimal medium. To over-produce the remaining 25 metabolites, we suggest a novel approach, this time focused on engineering the producer strain  via gene knockouts to couple the production of a metabolite of interest with the production of a proxy metabolite for which a biosensor design has already been found . The latter approach is predicted to improve the potential production and secretion rates of several metabolites.In this paper, we describe a computational method for designing microbial biosensors that can be used to perform high-throughput measurements of the concentration of various small molecules. Applying our method to design biosensors based on A major limitation of current constraint-based rational design approaches in metabolic engineering is that they all aim to couple the production of a chemical of interest with biomass formation, such that evolutionary pressure towards growth rate maximization would lead to increased chemical production rates E. coli , which is a common target of metabolic engineering experiments and has a highly accurate metabolic network model. Considering the growing interest computational approaches in metabolic engineering and the current rapid reconstruction of metabolic networks  is a mathematical modeling approach for metabolic networks that utilizes knowledge of the network structure together with constraints on its possible behaviors, to predict possible functional metabolic states. Mass-balance constraints imposed by stoichiometry in a chemical network at steady state enforce the sum of all production and consumption rates of each metabolite to be zero:S denotes a stoichiometric matrix in which ijS corresponds to the stoichiometric coefficient of metabolite i in reaction j. S dimensions are n is the number of metabolites in the network and m is the number of reactions. m-dimensional vector of flux rates, where j at steady state. Additional constraints, including those pertaining to the availability of nutrients in the growth media or to the maximal flux that can be supported by specific enzymes can be introduced via the following inequality:Φ that represents the phenotypic potential of an organism. For an underdetermined system, as is typically the case in models of cellular metabolism Φ is a convex set in the m-dimensional space of fluxes Flux Balance Analysis (FBA) is a particular CBM method that assumes that the network is regulated to maximize a certain cellular function Taken together, the constraints limit the allowable functional states of a metabolic network. In mathematical terms, the range of allowable network states is described by a solution space C is present in the spent media and no growth when it is absent. The problem is formulated as following:The biosensor design method is based on a bi-level optimization problem that searches for gene knockouts such that a feasible flux distribution that satisfies stoichiometric mass-balance, reaction directionality, and knockout constraints, will enable high growth rate when chemical i'th reaction is represented by k . The uptake of the sensed chemical is enabled only for flux distribution Stoichiometric mass-balance, enzyme directionality and knockout constraints are enforced for the flux distribution Figure S1The predicted growth rate of the D-xylose (a) and D-galactose (b) biosensors, as a function of sensed chemical update rate, under both poor and rich media. As shown, the growth yield (represented by the slope of the curve) of the D-xylose biosensor significantly differ between poor and rich spent media. Hence if the D-xylose biosensor is grown after a minimal medium is supplemented to the spent medium, the potential secretion of additional metabolites by the producer strain may affect its biomass yield, leading to inaccurate estimation of the chemical concentration  to the spent. On the other hand, the D-galactose biosensor is predicted to have the same biomass yield in both poor and rich medium, facilitating the direct quantification of chemical concentration also in poor medium.(TIF)Click here for additional data file.Table S1The specific details of the predicted knockout combinations for each bio-sensor.(XLS)Click here for additional data file.Table S2Secretion rates of chemical as predicted by OptKnock and RobustKnock.(XLS)Click here for additional data file.Table S3Secretion rates of chemical (using different proxies) as predicted by OptKnock-proxy and RobustKnock-proxy.(XLS)Click here for additional data file.


Tactile perception is typically considered the result of cortical interpretation of afferent signals from a network of mechanical sensors underneath the skin. Yet, tactile illusion studies suggest that tactile perception can be elicited without afferent signals from mechanoceptors. Therefore, the extent that tactile perception arises from isomorphic mapping of tactile afferents onto the somatosensory cortex remains controversial. We tested whether isomorphic mapping of tactile afferent fibers onto the cortex leads directly to tactile perception by examining whether it is independent from proprioceptive input by evaluating the impact of different hand postures on the perception of a tactile illusion across fingertips. Using the Cutaneous Rabbit Effect, a well studied illusion evoking the perception that a stimulus occurs at a location where none has been delivered, we found that hand posture has a significant effect on the perception of the illusion across the fingertips. This finding emphasizes that tactile perception arises from integration of perceived mechanical and proprioceptive input and not purely from tactile interaction with the external environment. Activity in the somatosensory cortex has been directly linked to conscious tactile perception The CRE is a perceptual phenomenon where rapidly applied stimuli can induce the perception of a stimulus at a location where none was applied Illusory Rabbit Train, Motion Bias Train, Negative Control Train  stimuli on the associated skin region Adducted posture  we found that hand posture significantly affected the perception of a mislocalization onto this fingertip. Specifically we found that in five of the nine postures in this study that the CRE induced mislocalization of the attractee stimulus onto the middle fingertip. However, in the remaining four postures  the Illusory Rabbit and Motion Bias Trains induced a similar rate of mislocalization onto the middle fingertip, indicating that the CRE was not induced and only the Tau effect was needed to explain the mislocalization rate. Because of the differences in the presence of the CRE across these 9 postures, five inducing the CRE and four that were not susceptible to the CRE, we conclude that posture can significantly affect the ability to induce the CRE across fingertips.Goldreich There are two possible explanations for the failure of the Illusory Rabbit Train to induce the additional mislocalization of stimuli onto the middle fingertip in the All-Abducted posture, though the illusory and stimulated sites were collinear and equidistant from each other: (1) tactile interactions between stimulated fingertips and the presumed illusory fingertip aid in inducing the CRE, as in the Index-Abducted and Vulcan but not in the All-Abducted, and are absent in the All-Abducted; and/or (2) the increased space between the ‘cutaneous rabbit hops’ may lessen the CRE. Previous research has demonstrated that the illusory strength of the CRE  decreases as saltatory area increases In postures where the perceived motion of the stimulus train would not occur along a line, the Bayesian model predicts that mislocalization due to the Tau or CRE should not occur . Here, mislocalization of a stimulus onto the middle fingertip would force the perceptual ‘rabbit’ to jump out of its expected trajectory, along the line between the stimulated sites, and onto the non-collinear middle fingertip. Because this should result in a contradiction between the expectation of where the ‘rabbit’ should jump to (based on the direction of the stimuli) and the spatial location of the middle fingertip, the CRE and Tau effects are less likely to occur. However this is not what we observed. We found that mislocalization due to the CRE did not occur in the Index-, Middle-, and Ring-Flexed postures, but in the Middle-Extended posture the mislocalization attributable to the CRE was perceived at similar levels to those where the fingertips were collinear. The most likely explanation of this is that the collinearity of stimulated sites is more important than the collinearity of the expected trajectory of the illusory mislocalization, i.e. the posture of the stimulated sites are more important to determining whether or not illusory phenomena will influence the perception than the posture/position of the unstimulated (expected illusory) site. In the Middle-Flexed posture there was an overall high rate of mislocalization of stimuli onto the middle fingertip due to the Illusory Rabbit Train in comparison to the Index- and Ring-Flexed. Though there was an influential subject in the Middle-Flexed posture, the similar rates of mislocalization under Illusory Trains suggest that this posture may be more similar to the Middle-Extended posture than the Index- and Ring-Flexed postures. Together these data indicate postures where the stimulated sites are collinear are more likely to allow for mislocalization of stimulus location onto the unstimulated (expected illusory) site than postures where the stimulated sites are non-linear regardless of the unstimulated site's position relative to the stimulated sites.Though evidence exists that the perceptual basis for the CRE is found in unimodal tactile maps located in area 3b of somatosensory cortex n = 14) participated in this study. Subjects were selected for participation from the greater Phoenix community if they were without history of neurological disease or current peripheral neurological injury  that might affect their ability to perceive stimuli on their right hands. All subjects were familiar with experiencing electrotactile stimuli on their fingertips from prior experiences in this laboratory or others. However, none of the subjects were familiar with the CRE, the electrotactile stimulation trains, or the stimulation paradigm used in these experiments. Written informed consent documents were reviewed and signed by all participants before the experimental session began. These documents and procedures were previously reviewed and approved by the Institutional Review Board at Arizona State University, and were in accordance with the Declaration of Helsinki.Subjects  at random to the digital stimulator and onto the subject. Veridical Rabbit Trains consisted of two pulses sent to the index, middle, ring, and little fingertip, ‘D2-D3-D4-D5’, at the timing described above. Illusory Rabbit Trains consisted of stimuli at ‘D2-D2-D4-D5’. The Motion Bias Trains consisted of stimuli delivered to ‘D2-D4-D4-D5’and the Negative Control Trains consisted of stimuli delivered to D2 at 0 ms and D4 at 900ms .During setup and experimental trials, subjects were seated with their elbow bent and arm comfortably resting on a desk in front of them. Subjects were instructed that they could position their forearm and hand in front of them in a comfortable position. Throughout the trial subjects had full view of their hand and fingertips and a reference figure noting the names of the fingertip sites. The desk contained a computer monitor and a mouse, which the subject used to send the stimuli and record their responses. The monitor displayed a Labview® user interface that prompted subjects with appropriate controls to enter their responses, proceed to the next trial and send the next stimulus train. After clicking the button to deliver the next stimulus train, the program would select a train from a randomized rubric and send the appropriately timed train information to the digital stimulator. Once the subject received the electrical stimuli, the proper response types would appear on the screen allowing the subject recorded their response and then continue on to the next frame, repeating the process.A two-factor factorial design with factors, stimulus train type  and posture  was chosen to design and analyze the data for this experiment. A factorial design was chosen instead of a repeated measures design because there were few differences in experience, training, or background of the subjects in this experiment which makes it unlikely that real differences between treatments would be confounded with inter-subject variance other than their perception of the CRE, which could not be separated by a repeated measure design. The experimental design was created and analyzed using Design-Expert® . Overall, 14 subjects were used in this experiment, 10 of the subjects performed three experimental postures while four subjects performed four experimental postures. Each subject performed the Adducted posture to establish a baseline for their perception of the CRE across their fingertips.The four stimulus train factor levels were the train types previously described: Veridical Rabbit, Illusory Rabbit, Motion Bias, and Negative Control Trains.There were 9 factor levels or hand postures considered in this experiment, Adducted, All-Flexed, Index-Flexed, Middle-Flexed, Middle-Extended , Ring-Flexed, Index-Abducted, Vulcan , and All-Abducted  to complete the experiment, totaling either 156 or 208 total stimulus trains per subject. Most experimental sessions took between 45 and 60 minutes to complete once electrodes setup began.Design and Analysis of ExperimentsData analysis was performed using Design-Expert® using the general factorial design described above using the percentage of correct subject responses to “Did the preceding stimulus train contain a stimulus on the middle fingertip, D3?” for analysis. Analysis Of Variance (ANOVA) statistics were computed for the two-factor factorial design (posture and stimulus train type). Additionally ANOVAs and Fisher's Least Significant Difference (LSD) tests were performed on each posture to compare between the stimulus train types within a posture because there were significant differences between the postures. Detailed explanation of factorial analysis can be found in,


When a fluorophore is placed in the vicinity of a metal nanoparticle possessing a strong plasmon field, its fluorescence emission may change extensively. Our study is to better understand this phenomenon and predict the extent of quenching and/or enhancement of fluorescence, to beneficially utilize it in molecular sensing/imaging.Plasmon field intensities on/around gold nanoparticles (GNPs) with various diameters were theoretically computed with respect to the distance from the GNP surface. The field intensity decreased rapidly with the distance from the surface and the rate of decrease was greater for the particle with a smaller diameter. Using the plasmon field strength obtained, the level of fluorescence alternation by the field was theoretically estimated. For experimental studies, 10 nm GNPs were coated with polymer layer(s) of known thicknesses. Cypate, a near infrared fluorophore, was placed on the outermost layer of the polymer coated GNPs, artificially separated from the GNP at known distances, and its fluorescence levels were observed. The fluorescence of Cypate on the particle surface was quenched almost completely and, at approximately 5 nm from the surface, it was enhanced ~17 times. The level decreased thereafter. Theoretically computed fluorescence levels of the Cypate placed at various distances from a 10 nm GNP were compared with the experimental data. The trend of the resulting fluorescence was similar. The experimental results, however, showed greater enhancement than the theoretical estimates, in general. The distance from the GNP surface that showed the maximum enhancement in the experiment was greater than the one theoretically predicted, probably due to the difference in the two systems.Factors affecting the fluorescence of a fluorophore placed near a GNP are the GNP size, coating material on GNP, wavelengths of the incident light and emitted light and intrinsic quantum yield of the fluorophore. Experimentally, we were able to quench and enhance the fluorescence of Cypate, by changing the distance between the fluorophore and GNP. This ability of artificially controlling fluorescence can be beneficially used in developing contrast agents for highly sensitive and specific optical sensing and imaging. Fluorophores have been indispensable optical signal mediators in optical sensing and imaging for a long time and, as an imaging modality, optical imaging has been important because of its higher sensitivity . The sigWhen a fluorophore is placed at a relatively short distance, e.g., within 10 nm, from a metal particle possessing a strong plasmon field, the electrons of the flurophore participating in the excitation/emission interact with the field. The interaction results in a change in the fluorescence emission level, i.e., quenching or enhancement. Establishing the relationship between the plasmon field and the resulting fluorescence level can be beneficial in developing highly efficacious optical contrast agents for bio-sensing/imaging. For example, conditional quenching of fluorescence may be effectively used for another form of sensing  . EnhanceIn terms of the scientific progress in manipulating the fluorescence of fluorophores by metal nanoparticles, the quenching phenomena -12 appeaWe have theoretically studied the changes in the excitation decay rate and the quantum yield of a fluorophore that are caused by the plasmon field on/around a GNP. Fluorescence levels of a near infrared (NIR) fluorophore Cypate placed at various distances from the GNP surface were experimentally measured and compared with those obtained by the theoretical study.We hope that our study results will be helpful for improving the performance of the fluorescence contrast agents.p) at a position r, generated by an incident light (Eo) by a metal particle  coated with a shell , in a surrounding medium, can be described as in Eq. 1. For our study, we are assuming that the system has an azimuthal symmetry  at a thickness of 0, 1, 2 or 3 nm. For all cases, within the polymer layers, the field strengths are lower than the ones without. If one intends to place fluorophores inside the polymer layer then one should be aware that the plasmon field strength at the same distance from the GNP with a polymer layer is significantly lower than that of a bare GNP. The field strength immediately outside the coating is slightly higher than that of a bare GNP but the difference is minor. It should be noted that some metal shells can increase the field strength  was performed. As can be seen in Figure 0-3-(PAH-Cy) were measured at the excitation and emission wavelengths of 780 and 830 nm, respectively.Next, the relationship between the layer thickness on the GNP surface and the fluorescence of PAH-Cy was studied. For all samples, the Cypate concentration was adjusted to 30 μM. Then, the fluorescence intensities of GNP-Cypate, GNP-(PAH-Cy) and GNP-(PAH/PSS)Figure 2-(PAH-Cy). As can be seen in Figure 2-(PAHCy), fluorescence enhancement slowly disappeared with the removal of gold  . We thend Figure . After tNext, we plotted the theoretical Figure  and expeo) secreted by the target cancer cell. The long spacer should be biocompatible and biochemically stable. Its length should be such that the Cypate fluorescence is maximally enhanced. The GNP also includes a cancer targeting biomolecule (red arrow), as well as being coated with a biocompatible, hydrophilic polymer layer  chain. Ideally, after administering the entity to a patient and prior to finding the cancer, the entity emits little or no fluorescence because the short spacer ensures Cypate to be within the distance for fluorescence quenching by the GNP. Once it arrives at the cancer site, the targeting molecule reacts with a receptor on the cancer cells  the metal type of the particle in case metals other than gold are used. The dielectric permittivity of the metal determines the plasmon field distribution; (2) the nanoparticle size, i.e., field strength and the enhancement of the excitation decay rate depends on the particle size; (3) the wavelength (or fluorophore) to be used. The field strength depends upon the excitation wavelength, and the level of absorption of the emission light by the nanoparticle varies depending upon the emission wavelength; (4) the intrinsic quantum yield of the flurophore: It is one of the major factors that determine the quantum yield of the fluorophore placed near the nanoparticle; (5) the placement of a shell on the surface. The plasmon field distribution may change significantly depending on the material properties of the shell on the particle.In designing effective optical contrast agents, using both theoretical and experimental results on the relationship between the fluorescence of a fluorophore and the plasmon field strength  will be highly beneficial. For the researchers who plan to use this concept in practice, it is suggested that they first theoretically estimate the plasmon field distribution on/around the metal nanoparticle for a particular set of the system with a particular set of parameters . Once they have a set of experimental relationships for a particular system, they may be able to predict the relationships for another system using the theory, instead of performing many sets of experiments.We have also performed experimental studies on fluorescence changes of Cypate, an NIR fluorophore, by placing it at various distances from a GNP. For the studies, 10 nm GNPs were coated with polymer layers at known thicknesses and a Cypate layer was placed outside the polymer layers. The level of Cypate fluorescence was then correlated with the distance from the GNP surface . Fluorescence became almost completely quenched on the particle surface and approximately 17 times stronger than without GNP, at ~4.5 nm from the GNP surface. As the distance increased further, the enhancement decreased. The results of this study confirm that the plasmon field both quenches and enhances the fluorescence and the effect is strongly dependent on the distance from the particle surface .After a thorough theoretical analysis and experimental verification on the relationship between the fluorescence of a fluorophore and a GNP, one can use the relationship to produce novel optical contrast agents with high sensitivity and specificity.• Fluorescence of a fluorophore can be artificially altered by metal nanoparticles. Factors that can be manipulated to obtain a desired fluorescence are: the metal type and size of the nanoparticle, and distance between the fluorophore and the particle.• The quenching or enhancement of the fluorescence of a fluorophore highly depends upon the excitation and emission wavelengths of the fluorophore.• Theoretical prediction of the fluorescence may be beneficially used, at an initial stage of development, in designing a fluorophore-nanoparticle contrast agent, with thorough experimental verification in a later stage.• Enhancing fluorescence of FDA approved, NIR fluorophores by GNPs may be highly beneficial for medical imaging.o: intrinsic quantum yield; TEM: transmission electron microscopyCy: Cypate; DLS: dynamic light scattering; Em: emission; Ex: excitation; FITC: fluorescein isothiocyanate; FRET: fluorescence resonance energy transfer; GNP: gold nanoparticle; ICG: Indocyanine Green; NIR: near infrared; PAH: poly; PAH-Cy: Cypate conjugated poly; PAH/PSS: poly/poly(sodium-4-styrene sulfonate) bi-layer; PSS: poly(sodium-4-styrene sulfonate); q: quantum yield; qA patent application was filed with the content of this article, through the University of Louisville. There is no other competing interest.KAK conducted the research design and completed the manuscript, JW conducted the theoretical studies, JBK provided consultation on the mathematical model and obtained TEM images, and SA developed the fluorophore Cypate. All authors read and approved final manuscript.


We describe the use of Java Pattern Finder (JaPaFi) to identify short (<100 nt) highly conserved sequences in a series of poxvirus genomes. The algorithm utilizes pattern matching to identify approximate matches appearing at least once in each member of a set of genomes; a key feature is that the genomes do not need to be aligned. The user simply specifies the genomes to search, minimum length of sequences to find and the maximum number of mismatches and indels allowed. Many of the most highly conserved segments contain poxvirus promoter elements. In compIn studies of non-coding regions, sequences that display particularly high degrees of conservation are regarded as good candidates for regulating gene expression ,3. This de novo (as opposed to searching for matches to a known sequence) without requiring an alignment of the DNA sequences being investigated. Classically, search tools such as BLAST have been used to search for sequence matches; however, since BLAST, PROSITE and other database search tools require input query sequences they are not appropriate for the identification of previously unknown motif-like matches. It is important to note that unlike BLAST, JaPaFi has no minimum word size that must be matched and indels may occur in part of the set of differences between the sequence patterns; thus JaPaFi can detect smaller patterns than a tool based on a BLAST-type algorithm. Also, with any alignment-based method, no matter how sophisticated the alignment algorithm, problems arise in the face of non-colinearity, as is the case with poxviruses. The tools that are currently available, such as WABA (Wobble Aware Bulk Aligner) . To. To25]. In some cases, such as in Hit04, back-to-back promoters accounted for almost the whole length of the hit, while in others, lengthy stretches of highly conserved sequence flank the promoter elements .3.4.E-value that scores the overall match between the motif and all instances of this motif in the query sequences [E-values are used to judge the significance of the motifs by comparing them to a user-specified threshold E-value [E-value as guidance, a threshold E-value of 10 was used [−1, it is the only motif identified that can be considered statistically significant by virtue of being within two orders of magnitude of NCBI’s default threshold e-value of 10  gene, which encodes a promoter-binding protein with DNA-dependent ATPase activity that is involved in activating transcription of early genes in poxviruses . The HitHit06 was found in the RNA Polymerase-Associated Protein (RAP94), a 94 kDa viral polypeptide that associates with DNA-dependent RNA polymerase molecules, which is believed to confer specificity to the RNA polymerase for promoters of early genes through its association with VETF . The amim081R were examined  codons .The generation of truncated proteins has not been previously observed in poxviruses . Similar4.The discovery of the conserved sequence element (CSE) raised the question of whether or not a 42 nt sequence that is perfectly or near-perfectly conserved in seven different poxviruses from four different genera is unusual. In this study, we have discovered, using the JaPaFi program, that there are in fact a significant number of comparable sequences in this set of genomes. Thus, the CSE is actually part of a larger conserved sequence that is only one of 11 hit sequences that are unusually well conserved among these genomes. Nine of 11 of these hits contain conserved promoter elements, as summarized below, and we hypothesized that the presence of particularly well-conserved promoters partially accounted for most of the conservation observed in these hits. We developed a scoring method based on position scores that represent the degree of conservation at each position of a sequence alignment, as observed in alignment Logos, and we found that the conservation scores for the hits were significantly higher than those obtained for a control set of 10 different promoters.The 11 hits were analyzed for conserved functions using a number of sequence-based bioinformatics methods, including promoter element searches based on the consensus sequences of the three classes of poxvirus promoters and motif searches within the hits themselves. We found that Hit01 contains the CSE, which was later shown to act as a promoter in poxviruses. Hit01 also includes 10 nts upstream of the beginning of the CSE, which is likely explained by the fact that these JaPaFi searches allowed more differences between the matching regions. The flanking region around the CSE is believed to be part of the promoter for a cytoplasmic protein gene (MYXV m018L), for which translation initiates downstream of the hit. Hits 02, 04, 07 and 10 all contain bidirectional promoters, where promoter elements for two divergently transcribed, opposite strand genes overlap in the non-coding sequence between the genes. In the cases of Hits 04 and 07, these bidirectional promoters make up almost the entire hit, which may explain the conservation of these hits, since the promoter elements constrain the nucleotide makeup of these regions. Hits 02 and 10, however, contain lengthy stretches flanking the bidirectional promoters that are also highly conserved, suggesting that these regions may have conserved functions in addition to the bidirectional promoters. Hits 03, 08 and 09 also contain promoters, which may account for parts of the conservation observed in these hits; however, the majority of each of these hits falls within the coding sequence of nearby genes. This results in two constraints on these sequences; protein sequence conservation as a result of the conservation of these genes, and DNA sequence conservation due to conserved promoter elements. Hits 05 and 06 fell entirely within coding sequences although motifs resembling poxvirus promoters were identified in both. These motifs raised the question of whether or not protein products were produced from transcripts initiating at these alternate start sites. The hit sequences also raised the question of why conservation was observed at the DNA level when it is not required in order for the protein sequence to be conserved. The codon degeneracy of the nucleotides in these protein sequences showed that Hit05 is mostly made up of codons with two-fold degeneracy, limiting the possible variation at the DNA level to a degree that might partially explain the conservation of the hit. Hit06, however, consists mostly of codons with three- to six-fold degeneracy. Since its protein sequence can be encoded by a greater variety of DNA sequences, its high level of conservation suggests that there might be another, non-coding, function associated with this DNA sequence. The protein sequences of neither of these hits were found to be a part of known conserved protein domains when queried against the Prosite database. Therefore, the high degree of conservation observed at the DNA level remains unexplained, and other novel conserved functions may yet exist in the DNA. A single promoter element was identified in Hit11, acting on the DNA Processivity Factor gene. However, this only accounted for part of the sequence, suggesting that the remaining portion may have an unknown conserved function.Searches identified a motif surrounding the translation starts sites of late genes. This motif brings together the highly conserved TAAAT motif that makes up the initiator site of late promoters and the Kozak sequence, suggesting that it is functional in the DNA as a promoter and mRNA to promote translation.Although consensus sequences exist for poxvirus promoters, these sequences allow for a great deal of variation since, by nature, the promoters themselves vary in sequence. Therefore it should be noted that although the presence of conserved promoter elements has been considered a suitable explanation for the conservation of the regions of the hits in which these promoter elements fall, they are unusually well conserved even for poxvirus promoters.Since this analysis has been conducted entirely on the set of seven poxvirus genomes used in Brunetti’s analysis , a logicSimilar analyses can be conducted on different virus families to identify sequences that may have very different family-specific conserved functions. Coronaviruses, for instance, contain a ribosomal signal in the genome sequence between two ORF. This signal forms an RNA pseudoknot, causing a frame shift that enables the translation of a different ORF. Applying JaPaFi to various sets of viral genomes might identify other DNA or RNA sequences with conserved functions.