Addressing inter-gene heterogeneity in maximum likelihood phylogenomic analysis: yeasts revisited

Phylogenomic approaches to the resolution of inter-species relationships have become well established in recent years. Often these involve concatenation of many orthologous genes found in the respective genomes followed by analysis using standard phylogenetic models. Genome-scale data promise increased resolution by minimising sampling error, yet are associated with well-known but often inappropriately addressed caveats arising through data heterogeneity and model violation. These can lead to the reconstruction of highly-supported but incorrect topologies. With the aim of obtaining a species tree for 18 species within the ascomycetous yeasts, we have investigated the use of appropriate evolutionary models to address inter-gene heterogeneities and the scalability and validity of supermatrix analysis as the phylogenetic problem becomes more difficult and the number of genes analysed approaches truly phylogenomic dimensions. We have extended a widely-known early phylogenomic study of yeasts by adding additional species to increase diversity and augmenting the number of genes under analysis. We have investigated sophisticated maximum likelihood analyses, considering not only a concatenated version of the data but also partitioned models where each gene constitutes a partition and parameters are free to vary between the different partitions (thereby accounting for variation in the evolutionary processes at different loci). We find considerable increases in likelihood using these complex models, arguing for the need for appropriate models when analyzing phylogenomic data. Using these methods, we were able to reconstruct a well-supported tree for 18 ascomycetous yeasts spanning about 250 million years of evolution.     

Mitochondrial heterogeneity during staurosporine-induced apoptosis in HL60 cells: analysis at the single cell and single organelle level

BACKGROUND: Apoptosis is a complex phenomenon during which several events occur. A growing interest exists on the role and functionality of mitochondria during this type of cell death. The responsibility of modifications in mitochondrial membrane potential (Delta Psi) in triggering apoptosis is under investigation. METHODS: We evaluated Delta Psi changes in HL60 cells treated with staurosporine (STS). Flow cytometry and confocal microscopy have been used to analyze samples stained with two Delta Psi-sensitive probes, JC-1 and MitoTrackertrade mark Red CMXRos. RESULTS: At the cellular level, we found heterogeneic behavior. Indeed, after STS treatment, some cells displayed typical markers of apoptosis and a collapse in Delta Psi. Others were apoptotic with no changes in Delta Psi, others changed Delta Psi without being apoptotic, and others were healthy. The same heterogeneic response to STS was found at the single organelle level. In a given cell, some mitochondria were depolarized whereas others were not. CONCLUSION: In this model of apoptosis, changes in Delta Psi can be different among cells of the same type and among different organelles of the same cell. The collapse in Delta Psi is thus a heterogeneic phenomenon that seems to be an ancillary event following the irreversible phase of the apoptotic process.     

GoIFISH: a system for the quantification of single cell heterogeneity from IFISH images

Molecular analysis has revealed extensive intra-tumor heterogeneity in human cancer samples, but cannot identify cell-to-cell variations within the tissue microenvironment. In contrast, in situ analysis can identify genetic aberrations in phenotypically defined cell subpopulations while preserving tissue-context specificity. GoIFISH is a widely applicable, user-friendly system tailored for the objective and semi-automated visualization, detection and quantification of genomic alterations and protein expression obtained from fluorescence in situ analysis. In a sample set of HER2-positive breast cancers GoIFISH is highly robust in visual analysis and its accuracy compares favorably to other leading image analysis methods. GoIFISH is freely available at www.sourceforge.net/projects/goifish/.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0442-y) contains supplementary material, which is available to authorized users.     

Microfluidics for single cell analysis

Substantial evidence shows that the heterogeneity of individual cells within a genetically identical population can be critical to their chance of survival. Methods that use average responses from a population often mask the difference from individual cells. To fully understand cell-to-cell variability, a complete analysis of an individual cell, from its live state to cell lysates, is essential. Highly sensitive detection of multiple components and high throughput analysis of a large number of individual cells remain the key challenges to realise this aim. In this context, microfluidics and lab-on-a-chip technology have emerged as the most promising avenue to address these challenges. In this review, we will focus on the recent development in microfluidics that are aimed at total single cell analysis on chip, that is, from an individual live cell to its gene and proteins. We also discuss the opportunities that microfluidic based single cell analysis can bring into the drug discovery process.     

Modelling the individual cell lag phase. Isolating single cells: protocol development

AIMS: To develop a protocol to isolate single cells in wells of a microtitre plate, having a high certainty of individual cells, combined with a sufficient yield. METHODS AND RESULTS: Single cells were obtained using 1/2 dilution series in microtitre plates. Seventy-two Lactococcus lactis dilution series were checked by plate counting. When the last five columns of the plates were observed, the chance of having one single cell was 80%, while the yield was 75 wells containing cells. A simulation model confirmed these results. This method was compared with the commonly applied method. CONCLUSIONS: This method makes it possible to combine a higher chance of having one cell in a microtitre well with a slightly higher yield. SIGNIFICANCE AND IMPACT OF THE STUDY: A tool is developed to isolate single cells to provide a suitable base for investigating and modelling the individual cell lag phase.     

Limiting dilution analysis of T helper cell heterogeneity: a single class of T cell makes both IL 2 and IL 3

We have previously described a limiting dilution assay (LDA) for estimating the frequency, in the spleens of unprimed mice, of alloantigen-responsive cells that, together with their immediate clonal progeny, can produce interleukin 2 (IL 2) in short-term culture. In this paper, we provide further evidence that the limiting cell in these cultures is, in fact, the immediate precursor of the IL 2-producing cell rather than merely a participant in a multicellular cascade that ultimately leads to production of this lymphokine. We also demonstrate the usefulness of the LDA method for estimating the frequency of the limiting cell for production of IL 3. By analyzing the supernatants of these short-term microcultures for both IL 2 and IL 3, we show that essentially all wells that produce IL 3 also produce IL 2. Furthermore, the amount of IL 2 produced in any individual well correlates strongly with the IL 3 production in the same well. Our data suggest that both these lymphokines are produced by a single class of T cell, and further that the regulatory events that control IL 2 generation in allostimulated helper cells act to control IL 3 levels in parallel.     

Cell cycle analysis of Taxus suspension cultures at the single cell level as an indicator of culture heterogeneity

Single cell growth and division was measured via flow cytometry in order to characterize the metabolic variability of Taxus cuspidata suspension cultures, which produce the valuable secondary metabolite Taxol. Good agreement was observed between the cell cycle distribution and biomass accumulation over the batch culture period. Specific growth rates of 0.13 days(-1) by fresh weight and 0.15 days(-1) by dry weight were measured. Elicitation with methyl jasmonate (MJ) significantly decreased both cell cycle progression and biomass accumulation, as the specific growth rate decreased to 0.027 days(-1) by fresh and dry weight. Despite the decrease in biomass accumulation for MJ elicited cultures, sucrose utilization was not significantly different from control cultures. MJ elicitation also increased the accumulation of paclitaxel and other taxanes. The accumulation of upstream taxanes (baccatin III and 10-deactylbaccatin III) increased during exponential growth, reached a maximum around day 12, and then declined throughout the stationary phase. The paclitaxel concentration increased during both exponential growth and stationary phase, reaching a maximum around days 20-25. Throughout the culture period, greater than 70% of the cells were in G(0)/G(1) phase of the cell cycle. Studies using bromodeoxyuridine (BrdU) incorporation showed that approximately 65% of the Taxus cells are noncycling, even during exponential growth. Although the role of these cells is currently unknown, the presence of a large, noncycling subpopulation can have a significant impact on the utilization of plant cell culture technology for the large-scale production of paclitaxel. These results demonstrate that there is a high degree of metabolic heterogeneity in Taxus cuspidata suspension cultures. Understanding this heterogeneity is important for the optimization of plant cell cultures, particularly the reduction of production variability.     

Computational and experimental single cell biology techniques for the definition of cell type heterogeneity,interplay and intracellular dynamics

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Genome-wide linkage analysis of blood pressure under locus heterogeneity

We describe a method for mapping quantitative trait loci that allows for locus heterogeneity. A genome-wide linkage analysis of blood pressure was performed using sib-pair data from the Framingham Heart Study. Evidence of linkage was found on four markers (GATA89G08, GATA23D06, GATA14E09, and 049xd2) at a significance level of 0.01. Two of them (GATA14E09 and 049xd2) seem to overlap with linkage signals reported previously, while the other two are not linked to any known signals.     

Single cell human genomic analyses: a way to refine the knowledge of cellular heterogeneity origins in individual subject

Single cell genomics performed on individual human subjects' tumors, neural tissues, and sperm samples revealed the existence of genetic heterogeneity arising through either mutations in exomes, deletions, recombinations, and duplications of DNA sequences, as well as aneuploidy. These genetic changes happen during cell cycles followed by cell division. The aim of this review is to strictly focus on single cell human genomics and intends to deliver information that can help to refine fundamental knowledge relating to genetic causes of cellular heterogeneity origins in both healthy and disease states. Allogenic heterogeneity as well as heterogeneity origins of cells possessing the same genome with different gene expression patterns is not the subject of this review. Future research still requires: a) improvement for complete and errorless DNA acquisition and sequencing of not only selected parts of the genome, and b) analyses of more samples that contain millions of cells. These data will deliver a more precise comparative representation of genetic diversity among single cells in an individual human subject. Consequently, we will be able to better distinguish between the role of genetic, versus epigenetic, and stochastic factors in the cellular diversity of over 30 trillion cells present in a human body.     

Microfluidic techniques for high throughput single cell analysis

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