During its life cycle, the amoebozoon Physarum polycephalum forms multinucleate plasmodial cells that can grow to macroscopic size while maintaining a naturally synchronous population of nuclei. Sporulation-competent plasmodia were stimulated through photoactivation of the phytochrome photoreceptor and the expression of sporulation marker genes was analyzed quantitatively by repeatedly taking samples of the same plasmodial cell at successive time points after the stimulus pulse. Principal component analysis of the gene expression data revealed that plasmodial cells take different trajectories leading to cell fate decision and differentiation and suggested that averaging over individual cells is inappropriate. Queries for genes with pairwise correlated expression kinetics revealed qualitatively different patterns of co-regulation, indicating that alternative programs of differential regulation are operational in individual plasmodial cells. At the single cell level, the response to stimulation of a non-sporulating mutant was qualitatively different as compared to the wild type with respect to the differentially regulated genes and their patterns of co-regulation. The observation of individual differences during commitment and differentiation supports the concept of a Waddington-type quasipotential landscape for the regulatory control of cell differentiation. Comparison of wild type and sporulation mutant data further supports the idea that mutations may impact the topology of this landscape.

Physarum polycephalum is a lower eukaryote belonging to the amoebozoa group of organisms that forms macroscopic, multinucleate plasmodial cells during its developmental cycle. Plasmodia can exit proliferative growth and differentiate by forming fruiting bodies containing mononucleate, haploid spores. This process, called sporulation, is controlled by starvation and visible light. To genetically dissect the regulatory control of the commitment to sporulation, we have isolated plasmodial mutants that are altered in the photocontrol of sporulation in a phenotypic screen of N-ethyl-N-nitrosourea (ENU) mutagenized cells. Several non-sporulating mutants were analyzed by measuring the light-induced change in the expression pattern of a set of 35 genes using GeXP multiplex reverse transcription-polymerase chain reaction with RNA isolated from individual plasmodial cells. Mutants showed altered patterns of differentially regulated genes in response to light stimulation. Some genes clearly displayed pairwise correlation in terms of their expression level as measured in individual plasmodial cells. The pattern of pairwise correlation differed in various mutants, suggesting that different upstream regulators were disabled in the different mutants. We propose that patterns of pairwise correlation in gene expression might be useful to infer the underlying gene regulatory network.

We analyzed the developmental switch to sporulation of a multinucleate Physarum polycephalum plasmodial cell, a complex response to phytochrome photoreceptor activation. Automatic construction of Petri nets from trajectories of differential gene expression in single cells revealed alternative, genotype-dependent interconnected developmental routes and identified metastable states, commitment points, and subsequent irreversible steps together with molecular signatures associated with cell fate decision and differentiation. Formation of transition-invariants in mutants that are locked in a proliferative state is remarkable considering the view that oncogenic alterations may cause the formation of cancer attractors. We conclude that the Petri net approach is useful to probe the Waddington landscape of cellular reprogramming, to disentangle developmental routes for the reconstruction of the gene regulatory network, and to understand how genetic alterations or physiological conditions reshape the landscape eventually creating new basins of attraction. Unraveling the complexity of pathogenesis, disease progression, and drug response or the analysis of attractor landscapes in other complex systems of uncertain structure might be additional fields of application.

Background Quantitative analysis of differential gene expression is of central importance in molecular life sciences. The Gene eXpression Profiling technology (GeXP) relies on multiplex RT-PCR and subsequent capillary electrophoretic separation of the amplification products and allows to quantify the transcripts of at least 35 genes with a single reaction and one dye. Results We provide a kinetic model of primer binding and PCR product formation as the rational basis for taking and evaluating calibration curves. The calibration procedure and the model predictions were validated with the help of a purposefully designed data processing workflow supported by easy-to-use Perl scripts for calibration, data evaluation, and quality control. We further demonstrate the robustness and linearity of quantification of individual transcripts at variable relative abundance of other co-amplified transcripts in a complex mixture of RNAs isolated from differentiating Physarum polycephalum plasmodial cells. Conclusions We conclude that GeXP analysis is a robust, sensitive, and useful method when the transcripts of tens to few hundred genes are to be precisely quantified in a high number of samples.