Cadmium elicits alterations in mitochondrial morphology and functionality in C3H10T1/2Cl8 mouse embryonic fibroblasts.

BACKGROUND: Cadmium is a widespread carcinogen. We previously showed that the administration of low CdCl2 doses for 24 h to healthy C3H10T1/2Cl8 mouse embryonic fibroblast cell line at the beginning of Cell Transformation Assay (CTA), up regulates genes involved in metal scavenging and antioxidant defense, like metallothioneines, glutathione S-transferases and heat shock proteins. Still, although most cells thrive normally in the following weeks, malignancy is triggered by CdCl2 and leads to the appearance of foci of transformed cells at the end of the CTA. In this work we aim at elucidating the early metabolic deregulation induced by cadmium, underlying healthy cell transformation into malignant cells. METHODS: Respiratory metabolism was investigated through Seahorse Agilent assays, while oxidative stress level was assessed through fluorescent probes; DNA damage was evaluated by Comet assay, and mitochondrial morphology was analyzed in confocal microscopy. RESULTS: Results show that the initial response to CdCl2 involves mitochondria rearrangement into a perinuclear network. However, SOD1 and SOD2 activities are inhibited, leading to increased superoxide anion level, which in turn causes DNA strand breaks. From the metabolic point of view, cells increase their glycolytic flux, while all extra NADH produced is still efficiently reoxidized by mitochondria. CONCLUSIONS: Our results confirm previously shown response against cadmium toxicity; new data about glycolytic increase and mitochondrial rearrangements suggest pathways leading to cell transformation. GENERAL SIGNIFICANCE: In this work we exploit the widely used, well known CTA, which allows following healthy cells transformation into a malignant phenotype, to understand early events in cadmium-induced carcinogenesis.

Cadmium-transformed cells in the in vitro cell transformation assay reveal different proliferative behaviours and activated pathways.

The in vitro Cell Transformation Assay (CTA) is a powerful tool for mechanistic studies of carcinogenesis. The endpoint is the classification of transformed colonies (foci) by means of standard morphological features. To increase throughput and reliability of CTAs, one of the suggested follow-up activities is to exploit the comprehension of the mechanisms underlying cell transformation. To this end, we have performed CTAs testing CdCl2, a widespread environmental contaminant classified as a human carcinogen with the underlying mechanisms of action not completely understood. We have isolated and re-seeded the cells at the end (6weeks) of in vitro CTAs to further identify the biochemical pathways underlying the transformed phenotype of foci. Morphological evaluations and proliferative assays confirmed the loss of contact-inhibition and the higher proliferative rate of transformed clones. The biochemical analysis of EGFR pathway revealed that, despite the same initial carcinogenic stimulus (1µM CdCl2 for 24h), transformed clones are characterized by the activation of two different molecular pathways: proliferation (Erk activation) or survival (Akt activation). Our preliminary results on molecular characterization of cell clones from different foci could be exploited for CTAs improvement, supporting the comprehension of the in vivo process and complementing the morphological evaluation of foci.

Objective scoring of transformed foci in BALB/c 3T3 cell transformation assay by statistical image descriptors.

In vitro cell transformation assays (CTAs) have been shown to model important stages of in vivo carcinogenesis and have the potential to predict carcinogenicity in humans. Advantages of CTAs are their ability of revealing both genotoxic and non-genotoxic carcinogens while reducing both experimental costs and the number of animals used. The endpoint of the CTA is foci formation, and requires classification under light microscopy based on morphology. Thus current limitations for the wide adoption of the assay partially depend on a fair degree of subjectivity in foci scoring. An objective evaluation may be obtained after separating foci from background monolayer in the digital image, and quantifying values of statistical descriptors which are selected to capture eye-scored morphological features. The aim of this study was to develop statistical descriptors to be applied to transformed foci of BALB/c 3T3, which cover foci size, multilayering and invasive cell growth into the background monolayer. Proposed descriptors were applied to a database of 407 foci images to explore the numerical features, and to illustrate open problems and potential solutions.

Image analysis and automatic classification of transformed foci.

Carcinogenesis is a multi-step process involving genetic alterations and non-genotoxic mechanisms. The in vitro cell transformation assay allows the monitoring of the neoplastic phenotype by foci formation in suitable cells (e.g. C3H10T1/2 mouse embryo fibroblasts) showing aberrant morphology of massive build-up, polar and multi-layered densely stained cells. The classification of transformed foci in C3H cells relies on light microscopy scoring by a trained human expert based on standard rules. This procedure is time-consuming and prone, in some cases, to subjectivity, thereby leading to possible over- or under-estimation of the carcinogenic potential of tested compounds. Herewith we describe the in vitro neoplastic transformation induced by B[a]P and CdCl2, and the development of a foci classifier based on image analysis and statistical classification. The image analysis system, which relies on 'spectrum enhancement', is quantitative and extracts descriptors of foci texture and structure. The statistical classification method is based on the Random Forest algorithm. We obtained a classifier trained by using expert's supervision with a 20% classification error. The proposed method could serve as a basis to automate the in vitro cell transformation assay.

The in vitro effect of gossypol and its interaction with salts on conidial germination and viability of Fusarium oxysporum sp. vasinfectum isolates.

AIMS: To assess the effect of different concentrations of gossypol (0, 2, 4, 10 and 20 mg l(-1)) in combination with NaCl and Na(2)SO(4) (20 mS cm(-1)) on the conidial germination and viability of Fusarium oxysporum f.sp. vasinfectum (Fov). METHODS AND RESULTS: A multinomial logistic model was developed to estimate the germination probability of Fov. The inhibitory effect was markedly evident at the two highest concentrations of gossypol; it varied among the isolates tested and with time, and it was attenuated by the presence of sodium salts. The inhibition was temporary as the germination probability increased after 8 h. Fluorescent staining revealed that gossypol either killed the conidia or retarded the elongation of the germ tubes. CONCLUSION: Fov showed the ability to overcome gossypol inhibition over time, and the inhibitory effect is reduced under saline conditions. Differential responses among Fov isolates to the presence of gossypol suggest that gossypol tolerance is genetically determined in the pathogen. SIGNIFICANCE AND IMPACT OF THE STUDY: This study suggests that selecting for high plant gossypol cultivars would have minimal effect on the overall Fov resistance of cotton. A new statistical model was developed to explore the statistical significance of plant-pathogen interactions.

The reduction of large molecular profiles to informative components using a genetic algorithm.

MOTIVATION: Molecular profiles (DNA fingerprints) may be used to allocate an individual of unknown membership to one among the known groups of a reference population. Time and costs of profile assessment may be reduced by identifying informative profile components (markers). RESULTS: A genetic algorithm (GA) is proposed to identify promising candidate markers from a pilot experiment in which observations are supposed to be without measurement error. The analysis of simulated datasets suggests reasonable values for GA parameters and confirms that the GA finds components of the profile showing association with the considered groups. Our GA may be used to perform a first screening of candidate markers to be included in subsequent experiments. AVAILABILITY: The 32-bit executable (Windows 95, 98 and NT) is available at http://www.ds.unifi.it/ approximately stefanin/bioinformatics.htm.

Bayesian estimation of range for microsatellite loci.

Microsatellite loci have become important in population genetics because of their high level of polymorphism in natural populations, very frequent occurrence throughout the genome, and apparently high mutation rate. Observed repeat numbers (alleles size) in natural populations and expectations based on computer simulations suggest that the range of repeat numbers at a microsatellite locus is restricted. This range is a key parameter that should be properly estimated in order to proceed with calculations of divergence times in phylogenetic studies and to better investigate the within- and between-population variability. The 'plug-in' estimate of range based on the minimum and maximum value observed in a sample is not satisfactory because of the relatively large number of alleles in comparison with typical sample sizes. In this paper, a set of data from 30 dinucleotide microsatellite loci is analysed under the assumption of independence among loci. Bayesian inference on range for one locus is obtained by assuming that constraints on range values exist as sharp bounds. Closed-form calculations and robustness revealed by our analysis suggest that the proposed Bayesian approach might be routinely used by researchers to classify microsatellite loci according to the estimated value of their allelic range.

APLOGEN: an object-oriented genetic algorithm performing Monte Carlo optimization.

Problem-solving and modelling within a biological context often need a level of descriptive accuracy that is unlikely to be capable of analytical treatment, especially if the mathematical background of the biologist is poor. Furthermore solver-model maintenance is often difficult without the availability of trained specialists. Better prospects are found in the genetic algorithm field. Genetic algorithms are a set of procedures formulated to solve complex problems without specifying rules for intermediate steps. This approach becomes feasible performing a Monte Carlo simulation of the natural evolution process, in which population improvement (search for solutions) in a considered environment (the specific problem domain) is achieved by following the genetic paradigm. Starting with a randomly constituted sample of individuals, drawn from the population of admissible values and expressed as binary strings, random mating brings about individuals of the next generation. Parents are chosen with a greater probability as the number of constraints violated by each individual becomes smaller. During the constitution of each generation the presence of some genetic operators causes the improvement of population diversity and its maintenance. Genetic operators are simple string transformation rules, generally independent of a specific context. We have developed the constant core of a minimal genetic algorithm, from which can be derived genetic problem-solvers in specific domains. An applicative example--a constrained matrix equation on signed integers--is also realized to show graphically the algorithm dynamics.