A semi-quantitative approach to assess biofilm formation using wrinkled colony development

Biofilms, or surface-attached communities of cells encapsulated in an extracellular matrix, represent a common lifestyle for many bacteria. Within a biofilm, bacterial cells often exhibit altered physiology, including enhanced resistance to antibiotics and other environmental stresses. Additionally, biofilms can play important roles in host-microbe interactions. Biofilms develop when bacteria transition from individual, planktonic cells to form complex, multi-cellular communities. In the laboratory, biofilms are studied by assessing the development of specific biofilm phenotypes. A common biofilm phenotype involves the formation of wrinkled or rugose bacterial colonies on solid agar media. Wrinkled colony formation provides a particularly simple and useful means to identify and characterize bacterial strains exhibiting altered biofilm phenotypes, and to investigate environmental conditions that impact biofilm formation. Wrinkled colony formation serves as an indicator of biofilm formation in a variety of bacteria, including both Gram-positive bacteria, such as Bacillus subtilis, and Gram-negative bacteria, such as Vibrio cholerae, Vibrio parahaemolyticus, Pseudomonas aeruginosa, and Vibrio fischeri. The marine bacterium V. fischeri has become a model for biofilm formation due to the critical role of biofilms during host colonization: biofilms produced by V. fischeri promote its colonization of the Hawaiian bobtail squid Euprymna scolopes. Importantly, biofilm phenotypes observed in vitro correlate with the ability of V. fischeri cells to effectively colonize host animals: strains impaired for biofilm formation in vitro possess a colonization defect, while strains exhibiting increased biofilm phenotypes are enhanced for colonization. V. fischeri therefore provides a simple model system to assess the mechanisms by which bacteria regulate biofilm formation and how biofilms impact host colonization. In this report, we describe a semi-quantitative method to assess biofilm formation using V. fischeri as a model system. This method involves the careful spotting of bacterial cultures at defined concentrations and volumes onto solid agar media; a spotted culture is synonymous to a single bacterial colony. This 'spotted culture' technique can be utilized to compare gross biofilm phenotypes at single, specified time-points (end-point assays), or to identify and characterize subtle biofilm phenotypes through time-course assays of biofilm development and measurements of the colony diameter, which is influenced by biofilm formation. Thus, this technique provides a semi-quantitative analysis of biofilm formation, permitting evaluation of the timing and patterning of wrinkled colony development and the relative size of the developing structure, characteristics that extend beyond the simple overall morphology.     

A statistical approach to quantification of genetically modified organisms (GMO) using frequency distributions

Background

According to Regulation (EU) No 619/2011, trace amounts of non-authorised genetically modified organisms (GMO) in feed are tolerated within the EU if certain prerequisites are met. Tolerable traces must not exceed the so-called ‘minimum required performance limit’ (MRPL), which was defined according to the mentioned regulation to correspond to 0.1% mass fraction per ingredient. Therefore, not yet authorised GMO (and some GMO whose approvals have expired) have to be quantified at very low level following the qualitative detection in genomic DNA extracted from feed samples. As the results of quantitative analysis can imply severe legal and financial consequences for producers or distributors of feed, the quantification results need to be utterly reliable.

Results

We developed a statistical approach to investigate the experimental measurement variability within one 96-well PCR plate. This approach visualises the frequency distribution as zygosity-corrected relative content of genetically modified material resulting from different combinations of transgene and reference gene Cq values. One application of it is the simulation of the consequences of varying parameters on measurement results. Parameters could be for example replicate numbers or baseline and threshold settings, measurement results could be for example median (class) and relative standard deviation (RSD). All calculations can be done using the built-in functions of Excel without any need for programming. The developed Excel spreadsheets are available (see section ‘Availability of supporting data’ for details). In most cases, the combination of four PCR replicates for each of the two DNA isolations already resulted in a relative standard deviation of 15% or less.

Conclusions

The aims of the study are scientifically based suggestions for minimisation of uncertainty of measurement especially in —but not limited to— the field of GMO quantification at low concentration levels. Four PCR replicates for each of the two DNA isolations seem to be a reasonable minimum number to narrow down the possible spread of results.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0407-x) contains supplementary material, which is available to authorized users.     

全球转基因作物种植状况及其分析

转基因植物近年来得到迅猛发展,影响日渐扩大。对近几年,尤其是2004年的全球转基因作物种植状况、未来的发展潜力及问题进行了较为系统的介绍和分析,结合我国的情况,对我国发展转基因作物的重点提出了相应的建议,认为应该重点发展优质、高产、抗逆转基因新品种。     

Qualitative and semi-quantitative analysis of gibberellins

A method for the qualitative and semi-quantitative analysis of gibberellins (GAs) was examined, and a systematic method consisting of six steps was established. By this method endogenous GAs in some organs of Pharbitis nil were quantitatively analysed.     

A symmetry approach to electrocardiogram analysis

A qualitative characteristics of a symmetry of correlations in ECG parameters has been studied in experiments on rats with the adaptation syndrome and hypertonic patients (I-II stages). A geometrical model of cardiac cycle shaped as a rectangular triangle with temporal and amplitude ECG parameters as catheti. A total correlation between the ECG parameters is given: QT--QRS/QT--PQ.RR--PQ/RR--QRS = R--P/R--T = 1,309. In healthy individuals, the deviation from the ideal proportion constitutes less than 5%, and in patients with cardiovascular diseases, the deviations are substantial.     

A stochastic approach to phyllotactic patterns analysis

A statistical method is presented to characterize the degree of order in phyllotactic systems. We developed equations allowing the theoretical estimation of the number of leaves regularly distributed (spiral or verticillate) in a partially random phyllotactic system. The equations are simple and accurate enough to make quantitative predictions concerning the organization of different phyllotactic patterns (verticillate, distichous, spiral and random). This method can bring out patterns that are not visible a priori on a planar representation of the shoot apex. As a case study, the method was applied to the quantitative analysis of the sho mutants recently produced by Itoh et al. [2000. SHOOT ORGANIZATION genes regulate shoot apical meristem organization and the pattern of leaf primordium initiation in Rice. Plant Cell 12, 2161-2174]. By using our method, it was possible to predict the number of leaves distributed in distichous or random patterns on these phyllotactic mutants.     

A multi-dimensional scaling approach to shape analysis

We propose an alternative to Kendall's shape space for reflectionshapes of configurations in with k labelled vertices, where reflection shape consistsof all the geometric information that is invariant under compositionsof similarity and reflection transformations. The proposed approachembeds the space of such shapes into the space of (k – 1) x (k – 1) real symmetricpositive semidefinite matrices, which is the closure of an opensubset of a Euclidean space, and defines mean shape as the naturalprojection of Euclidean means in on to the embedded copy of the shape space. This approachhas strong connections with multi-dimensional scaling, and themean shape so defined gives good approximations to other commonlyused definitions of mean shape. We also use standard perturbationarguments for eigenvalues and eigenvectors to obtain a centrallimit theorem which then enables the application of standardstatistical techniques to shape analysis in two or more dimensions.     

A DSRPCL-SVM approach to informative gene analysis

Microarray data based tumor diagnosis is a very interesting topic in bioinformatics. One of the key problems is the discovery and analysis of informative genes of a tumor. Although there are many elaborate approaches to this problem, it is still difficult to select a reasonable set of informative genes for tumor diagnosis only with microarray data. In this paper, we classify the genes expressed through microarray data into a number of clusters via the distance sensitive rival penalized competitive learning （DSRPCL） algorithm and then detect the informative gene cluster or set with the help of support vector machine （SVM）. Moreover, the critical or powerful informative genes can be found through further classifications and detections on the obtained informative gene clusters. It is well demonstrated by experiments on the colon, leukemia, and breast cancer datasets that our proposed DSRPCL-SVM approach leads to a reasonable selection of informative genes for tumor diagnosis.     

Time to relax GMO regulation in Europe

There is enough experience gained during 10 years of genetically modified (GM) crops application to seriously evaluate the ratio of risk to benefit and reduce the existing regulation in Europe. It does not evaluate benefit and the risk of the alternative situation when GM crops are not used. The precautionary principle is applied only to GM crops application, never to alternative solutions of, e.g., pest control. The Eurobarometer 2005 shows how propaganda inseminates public opinion with shameful nonsense. Voices asking for change of this politics come from the European Parliament, British ACRE, EuropaBio, even from Commission, scientists and other European sources, but also from Africa and other developing countries.     

A survival analysis approach to modeling human fecundity

Understanding conception probabilities is important not only for helping couples to achieve pregnancy but also in identifying acute or chronic reproductive toxicants that affect the highly timed and interrelated processes underlying hormonal profiles, ovulation, libido, and conception during menstrual cycles. Currently, 2 statistical approaches are available for estimating conception probabilities depending upon the research question and extent of data collection during the menstrual cycle: a survival approach when interested in modeling time-to-pregnancy (TTP) in relation to women or couples' purported exposure(s), or a hierarchical Bayesian approach when one is interested in modeling day-specific conception probabilities during the estimated fertile window. We propose a biologically valid discrete survival model that unifies the above 2 approaches while relaxing some assumptions that may not be consistent with human reproduction or behavior. This approach combines both the survival and the hierarchical models allowing investigators to obtain the distribution of TTP and day-specific probabilities during the fertile window in a single model. Our model allows for the consideration of covariate effects at both the cycle and the daily level while accounting for daily variation in conception. We conduct extensive simulations and utilize the New York State Angler Prospective Pregnancy Cohort Study to illustrate our approach. We also provide the code to implement the model in R software in the supplemental section of the supplementary material available at Biostatistics online.     

A Gibbs sampling approach to linkage analysis.

We present a Monte Carlo approach to estimation of the recombination fraction theta and the profile likelihood for a dichotomous trait and a single marker gene with 2 alleles. The method is an application of a technique known as 'Gibbs sampling', in which random samples of each of the unknowns (here genotypes, theta and nuisance parameters, including the allele frequencies and the penetrances) are drawn from their posterior distributions, given the data and the current values of all the other unknowns. Upon convergence, the resulting samples derive from the marginal distribution of all the unknowns, given only the data, so that the uncertainty in the specification of the nuisance parameters is reflected in the variance of the posterior distribution of theta. Prior knowledge about the distribution of theta and the nuisance parameters can be incorporated using a Bayesian approach, but adoption of a flat prior for theta and point priors for the nuisance parameters would correspond to the standard likelihood approach. The method is easy to program, runs quickly on a microcomputer, and could be generalized to multiple alleles, multipoint linkage, continuous phenotypes and more complex models of disease etiology. The basic approach is illustrated by application to data on cholesterol levels and an a low-density lipoprotein receptor gene in a single large pedigree.