Cascading transcriptional effects of a naturally occurring frameshift mutation in Saccharomyces cerevisiae

Gene-expression variation in natural populations is widespread, and its phenotypic effects can be acted upon by natural selection. Only a few naturally segregating genetic differences associated with expression variation have been identified at the molecular level. We have identified a single nucleotide insertion in a vineyard isolate of Saccharomyces cerevisiae that has cascading effects through the gene-expression network. This allele is responsible for about 45% (103/230) of the genes that show differential gene expression among the homozygous diploid progeny produced by a vineyard isolate. Using isogenic laboratory strains, we confirm that this allele causes dramatic differences in gene-expression levels of key genes involved in amino acid biosynthesis. The mutation is a frameshift mutation in a mononucleotide run of eight consecutive T's in the coding region of the gene SSY1 , which encodes a key component of a plasma-membrane sensor of extracellular amino acids. The potentially high rate of replication slippage of this mononucleotide repeat, combined with its relatively mild effects on growth rate in heterozygous genotypes, is sufficient to account for the persistence of this phenotype at low frequencies in natural populations.     

RT-qPCR based quantitative analysis of gene expression in single bacterial cells

Recent evidence suggests that cell-to-cell difference at the gene expression level is an order of magnitude greater than previously thought even for isogenic bacterial populations. Such gene expression heterogeneity determines the fate of individual bacterial cells in populations and could also affect the ultimate fate of populations themselves. To quantify the heterogeneity and its biological significance, quantitative methods to measure gene expression in single bacterial cells are needed. In this work, we developed two SYBR Green-based RT-qPCR methods to determine gene expression directly in single bacterial cells. The first method involves a single-tube operation that can analyze one gene from each bacterial cell. The second method is featured by a two-stage protocol that consists of RNA isolation from a single bacterial cell and cDNA synthesis in the first stage, and qPCR in the second stage, which allows determination of expression level of multiple genes simultaneously for single bacterial cells of both gram-positive and negative. We applied the methods to stress-treated (i.e. low pH and high temperature) Escherichia coli populations. The reproducible results demonstrated that the method is sensitive enough not only for measuring cellular responses at the single-cell level, but also for revealing gene expression heterogeneity among the bacterial cells. Furthermore, our results showed that the two-stage method can reproducibly measure multiple highly expressed genes from a single E. coli cell, which exhibits important foundation for future development of a high throughput and lab-on-chips whole-genome RT-qPCR methodology for single bacterial cells.     

An improved single-cell cDNA amplification method for efficient high-density oligonucleotide microarray analysis

A systems-level understanding of a small but essential population of cells in development or adulthood (e.g. somatic stem cells) requires accurate quantitative monitoring of genome-wide gene expression, ideally from single cells. We report here a strategy to globally amplify mRNAs from single cells for highly quantitative high-density oligonucleotide microarray analysis that combines a small number of directional PCR cycles with subsequent linear amplification. Using this strategy, both the representation of gene expression profiles and reproducibility between individual experiments are unambiguously improved from the original method, along with high coverage and accuracy. The immediate application of this method to single cells in the undifferentiated inner cell masses of mouse blastocysts at embryonic day (E) 3.5 revealed the presence of two populations of cells, one with primitive endoderm (PE) expression and the other with pluripotent epiblast-like gene expression. The genes expressed differentially between these two populations were well preserved in morphologically differentiated PE and epiblast in the embryos one day later (E4.5), demonstrating that the method successfully detects subtle but essential differences in gene expression at the single-cell level among seemingly homogeneous cell populations. This study provides a strategy to analyze biophysical events in medicine as well as in neural, stem cell and developmental biology, where small numbers of distinctive or diseased cells play critical roles.     

Geometry of the Gene Expression Space of Individual Cells

There is a revolution in the ability to analyze gene expression of single cells in a tissue. To understand this data we must comprehend how cells are distributed in a high-dimensional gene expression space. One open question is whether cell types form discrete clusters or whether gene expression forms a continuum of states. If such a continuum exists, what is its geometry? Recent theory on evolutionary trade-offs suggests that cells that need to perform multiple tasks are arranged in a polygon or polyhedron (line, triangle, tetrahedron and so on, generally called polytopes) in gene expression space, whose vertices are the expression profiles optimal for each task. Here, we analyze single-cell data from human and mouse tissues profiled using a variety of single-cell technologies. We fit the data to shapes with different numbers of vertices, compute their statistical significance, and infer their tasks. We find cases in which single cells fill out a continuum of expression states within a polyhedron. This occurs in intestinal progenitor cells, which fill out a tetrahedron in gene expression space. The four vertices of this tetrahedron are each enriched with genes for a specific task related to stemness and early differentiation. A polyhedral continuum of states is also found in spleen dendritic cells, known to perform multiple immune tasks: cells fill out a tetrahedron whose vertices correspond to key tasks related to maturation, pathogen sensing and communication with lymphocytes. A mixture of continuum-like distributions and discrete clusters is found in other cell types, including bone marrow and differentiated intestinal crypt cells. This approach can be used to understand the geometry and biological tasks of a wide range of single-cell datasets. The present results suggest that the concept of cell type may be expanded. In addition to discreet clusters in gene-expression space, we suggest a new possibility: a continuum of states within a polyhedron, in which the vertices represent specialists at key tasks.     

Computational integration of homolog and pathway gene module expression reveals general stemness signatures

The stemness hypothesis states that all stem cells use common mechanisms to regulate self-renewal and multi-lineage potential. However, gene expression meta-analyses at the single gene level have failed to identify a significant number of genes selectively expressed by a broad range of stem cell types. We hypothesized that stemness may be regulated by modules of homologs. While the expression of any single gene within a module may vary from one stem cell type to the next, it is possible that the expression of the module as a whole is required so that the expression of different, yet functionally-synonymous, homologs is needed in different stem cells. Thus, we developed a computational method to test for stem cell-specific gene expression patterns from a comprehensive collection of 49 murine datasets covering 12 different stem cell types. We identified 40 individual genes and 224 stemness modules with reproducible and specific up-regulation across multiple stem cell types. The stemness modules included families regulating chromatin remodeling, DNA repair, and Wnt signaling. Strikingly, the majority of modules represent evolutionarily related homologs. Moreover, a score based on the discovered modules could accurately distinguish stem cell-like populations from other cell types in both normal and cancer tissues. This scoring system revealed that both mouse and human metastatic populations exhibit higher stemness indices than non-metastatic populations, providing further evidence for a stem cell-driven component underlying the transformation to metastatic disease.     

Single Cell Analysis of a Bacterial Sender-Receiver System

Monitoring gene expression dynamics on the single cell level provides important information on cellular heterogeneity and stochasticity, and potentially allows for more accurate quantitation of gene expression processes. We here study bacterial senders and receivers genetically engineered with components of the quorum sensing system derived from Aliivibrio fischeri on the single cell level using microfluidics-based bacterial chemostats and fluorescence video microscopy. We track large numbers of bacteria over extended periods of time, which allows us to determine bacterial lineages and filter out subpopulations within a heterogeneous population. We quantitatively determine the dynamic gene expression response of receiver bacteria to varying amounts of the quorum sensing inducer N-3-oxo-C6-homoserine lactone (AHL). From this we construct AHL response curves and characterize gene expression dynamics of whole bacterial populations by investigating the statistical distribution of gene expression activity over time. The bacteria are found to display heterogeneous induction behavior within the population. We therefore also characterize gene expression in a homogeneous bacterial subpopulation by focusing on single cell trajectories derived only from bacteria with similar induction behavior. The response at the single cell level is found to be more cooperative than that obtained for the heterogeneous total population. For the analysis of systems containing both AHL senders and receiver cells, we utilize the receiver cells as ‘bacterial sensors’ for AHL. Based on a simple gene expression model and the response curves obtained in receiver-only experiments, the effective AHL concentration established by the senders and their ‘sending power’ is determined.     

Among‐lake reciprocal transplants induce convergent expression of immune genes in threespine stickleback

Geographic variation in parasite communities can drive evolutionary divergence in host immune genes. However, biotic and abiotic environmental variation can also induce plastic differences in immune function among populations. At present, there is little information concerning the relative magnitudes of heritable vs. induced immune divergence in natural populations. We examined immune gene expression profiles of threespine stickleback (Gasterosteus aculeatus) from six lakes on Vancouver Island, British Columbia. Parasite community composition differs between lake types (large or small, containing limnetic‐ or benthic‐like stickleback) and between watersheds. We observed corresponding differences in immune gene expression profiles among wild‐caught stickleback, using a set of seven immune genes representing distinct branches of the immune system. To evaluate the role of environmental effects on this differentiation, we experimentally transplanted wild‐caught fish into cages in their native lake, or into a nearby foreign lake. Transplanted individuals' immune gene expression converged on patterns typical of their destination lake, deviating from their native expression profile. Transplant individuals' source population had a much smaller effect, suggesting relatively weak genetic underpinning of population differences in immunity, as viewed through gene expression. This strong environmental regulation of immune gene expression provides a counterpoint to the large emerging literature documenting microevolution and genetic diversification of immune function. Our findings illustrate the value of studying immunity in natural environmental settings where the immune system has evolved and actively functions.     

The A1555G Mutation in the 12S rRNA Gene of Human mtDNA: Recurrent Origins and Founder Events in Families Affected by Sensorineural Deafness

The mtDNA variation of 50 Spanish and 4 Cuban families affected by nonsyndromic sensorineural deafness due to the A1555G mutation in the 12S rRNA gene was studied by high-resolution RFLP analysis and sequencing of the control region. Phylogenetic analyses of haplotypes and detailed survey of population controls revealed that the A1555G mutation can be attributed to >/=30 independent mutational events among the 50 Spanish families and that it occurs on mtDNA haplogroups that are common in all European populations. This indicates that the relatively high detection rate of this mutation in Spain is not due to sampling biases or to a single major founder event. Moreover, the distribution of these mutational events on different haplogroups is compatible with a random occurrence of the A1555G mutation and tends to support the conclusion that mtDNA backgrounds do not play a significant role in the expression of the mutation. Overall, these findings appear to indicate that the rare detection of this mutation in other populations is most likely due to inadequacy in patient ascertainment and molecular screening. This probable lack of identification of the A1555G mutation in subjects affected by sensorineural hearing loss implies that their maternally related relatives are not benefiting from presymptomatic detection and information concerning their increased risk of ototoxicity due to aminoglycoside treatments.     

Gene expression remodelling and immune response during adaptive divergence in an African cichlid fish

Variation in gene expression contributes to ecological speciation by facilitating population persistence in novel environments. Likewise, immune responses can be of relevance in speciation driven by adaptation to different environments. Previous studies examining gene expression differences between recently diverged ecotypes have often relied on only one pair of populations, targeted the expression of only a subset of genes or used wild‐caught individuals. Here, we investigated the contribution of habitat‐specific parasites and symbionts and the underlying immunological abilities of ecotype hosts to adaptive divergence in lake–river population pairs of the cichlid fish Astatotilapia burtoni. To shed light on the role of phenotypic plasticity in adaptive divergence, we compared parasite and microbiota communities, immune response, and gene expression patterns of fish from natural habitats and a lake‐like pond set‐up. In all investigated population pairs, lake fish were more heavily parasitized than river fish, in terms of both parasite taxon composition and infection abundance. The innate immune response in the wild was higher in lake than in river populations and was elevated in a river population exposed to lake parasites in the pond set‐up. Environmental differences between lake and river habitat and their distinct parasite communities have shaped differential gene expression, involving genes functioning in osmoregulation and immune response. Most changes in gene expression between lake and river samples in the wild and in the pond set‐up were based on a plastic response. Finally, gene expression and bacterial communities of wild‐caught individuals and individuals acclimatized to lake‐like pond conditions showed shifts underlying adaptive phenotypic plasticity.     

Resolving Cell Population Heterogeneity: Real-Time PCR for Simultaneous Multiplexed Gene Detection in Multiple Single-Cell Samples

Decoding the complexity of multicellular organisms requires analytical procedures to overcome the limitations of averaged measurements of cell populations, which obscure inherent cell-cell heterogeneity and restrict the ability to distinguish between the responses of individual cells within a sample. For example, defining the timing, magnitude and the coordination of cytokine responses in single cells is critical for understanding the development of effective immunity. While approaches to measure gene expression from single cells have been reported, the absolute performance of these techniques has been difficult to assess, which likely has limited their wider application. We describe a straightforward method for simultaneously measuring the expression of multiple genes in a multitude of single-cell samples using flow cytometry, parallel cDNA synthesis, and quantification by real-time PCR. We thoroughly assess the performance of the technique using mRNA and DNA standards and cell samples, and demonstrate a detection sensitivity of ∼30 mRNA molecules per cell, and a fractional error of 15%. Using this method, we expose unexpected heterogeneity in the expression of 5 immune-related genes in sets of single macrophages activated by different microbial stimuli. Further, our analyses reveal that the expression of one ‘pro-inflammatory’ cytokine is not predictive of the expression of another ‘pro-inflammatory’ cytokine within the same cell. These findings demonstrate that single-cell approaches are essential for studying coordinated gene expression in cell populations, and this generic and easy-to-use quantitative method is applicable in other areas in biology aimed at understanding the regulation of cellular responses.     

Gene duplications at the chemokine locus on mouse chromosome 4: multiple strain-specific haplotypes and the deletion of secondary lymphoid-organ chemokine and EBI-1 ligand chemokine genes in the plt mutation

The murine paucity of lymph node T cell (plt) mutation leads to abnormalities in leukocyte migration and immune response. The causative defect is thought to be a loss of secondary lymphoid-organ chemokine (SLC) expression in lymphoid tissues. We now find that the plt defect is due to the loss of both SLC and EBI-1 ligand chemokine (ELC) expression in secondary lymphoid organs. In an examination of the plt locus, we find that commonly used inbred mouse strains demonstrate at least three different haplotypes. Polymorphism at this locus is due to duplications of at least four genes, three of them encoding chemokines. At least two cutaneous T cell-attracting chemokine (CTACK), three SLC, and four ELC genes or pseudogenes are present in some haplotypes. All haplotypes share a duplication that includes two SLC genes, which demonstrate different expression patterns, a single functional ELC gene, and an ELC pseudogene. The plt mutation represents a deletion that includes the SLC gene expressed in secondary lymphoid organs and the single functional ELC gene, leaving only an SLC gene that is expressed in lymphatic endothelium and an ELC pseudogene. This lack of CCR7 ligands in the secondary lymphoid organs of plt mice provides a basis for their severe abnormalities in leukocyte migration and immune response.