6 resultados para Co-expression network
em CaltechTHESIS
Resumo:
Current measures of global gene expression analyses, such as correlation and mutual information-based approaches, largely depend on the degree of association between mRNA levels and to a lesser extent on variability. I develop and implement a new approach, called the Ratiometric method, which is based on the coefficient of variation of the expression ratio of two genes, relying more on variation than previous methods. The advantage of such modus operandi is the ability to detect possible gene pair interactions regardless of the degree of expression dispersion across the sample group. Gene pairs with low expression dispersion, i.e., their absolute expressions remain constant across the sample group, are systematically missed by correlation and mutual information analyses. The superiority of the Ratiometric method in finding these gene pair interactions is demonstrated in a data set of RNA-seq B-cell samples from the 1000 Genomes Project Consortium. The Ratiometric method renders a more comprehensive recovery of KEGG pathways and GO-terms.
Resumo:
Hematopoiesis is a well-established system used to study developmental choices amongst cells with multiple lineage potentials, as well as the transcription factor network interactions that drive these developmental paths. Multipotent progenitors travel from the bone marrow to the thymus where T-cell development is initiated and these early T-cell precursors retain lineage plasticity even after initiating a T-cell program. The development of these early cells is driven by Notch signaling and the combinatorial expression of many transcription factors, several of which are also involved in the development of other cell lineages. The ETS family transcription factor PU.1 is involved in the development of progenitor, myeloid, and lymphoid cells, and can divert progenitor T-cells from the T-lineage to a myeloid lineage. This diversion of early T-cells by PU.1 can be blocked by Notch signaling. The PU.1 and Notch interaction creates a switch wherein PU.1 in the presence of Notch promotes T-cell identity and PU.1 in the absence of Notch signaling promotes a myeloid identity. Here we characterized an early T-cell cell line, Scid.adh.2c2, as a good model system for studying the myeloid vs. lymphoid developmental choice dependent on PU.1 and Notch signaling. We then used the Scid.adh.2c2 system to identify mechanisms mediating PU.1 and Notch signaling interactions during early T-cell development. We show that the mechanism by which Notch signaling is protecting pro-T cells is neither degradation nor modification of the PU.1 protein. Instead we give evidence that Notch signaling is blocking the PU.1-driven inhibition of a key set of T-regulatory genes including Myb, Tcf7, and Gata3. We show that the protection of Gata3 from PU.1-mediated inhibition, by Notch signaling and Myb, is important for retaining a T-lineage identity. We also discuss a PU.1-driven mechanism involving E-protein inhibition that leads to the inhibition of Notch target genes. This is mechanism may be used as a lockdown mechanism in pro-T-cells that have made the decision to divert to the myeloid pathway.
Resumo:
Cdc48/p97 is an essential, highly abundant hexameric member of the AAA (ATPase associated with various cellular activities) family. It has been linked to a variety of processes throughout the cell but it is best known for its role in the ubiquitin proteasome pathway. In this system it is believed that Cdc48 behaves as a segregase, transducing the chemical energy of ATP hydrolysis into mechanical force to separate ubiquitin-conjugated proteins from their tightly-bound partners.
Current models posit that Cdc48 is linked to its substrates through a variety of adaptor proteins, including a family of seven proteins (13 in humans) that contain a Cdc48-binding UBX domain. As such, due to the complexity of the network of adaptor proteins for which it serves as the hub, Cdc48/p97 has the potential to exert a profound influence on the ubiquitin proteasome pathway. However, the number of known substrates of Cdc48/p97 remains relatively small, and smaller still is the number of substrates that have been linked to a specific UBX domain protein. As such, the goal of this dissertation research has been to discover new substrates and better understand the functions of the Cdc48 network. With this objective in mind, we established a proteomic screen to assemble a catalog of candidate substrate/targets of the Ubx adaptor system.
Here we describe the implementation and optimization of a cutting-edge quantitative mass spectrometry method to measure relative changes in the Saccharomyces cerevisiae proteome. Utilizing this technology, and in order to better understand the breadth of function of Cdc48 and its adaptors, we then performed a global screen to identify accumulating ubiquitin conjugates in cdc48-3 and ubxΔ mutants. In this screen different ubx mutants exhibited reproducible patterns of conjugate accumulation that differed greatly from each other, pointing to various unexpected functional specializations of the individual Ubx proteins.
As validation of our mass spectrometry findings, we then examined in detail the endoplasmic-reticulum bound transcription factor Spt23, which we identified as a putative Ubx2 substrate. In these studies ubx2Δ cells were deficient in processing of Spt23 to its active p90 form, and in localizing p90 to the nucleus. Additionally, consistent with reduced processing of Spt23, ubx2Δ cells demonstrated a defect in expression of their target gene OLE1, a fatty acid desaturase. Overall, this work demonstrates the power of proteomics as a tool to identify new targets of various pathways and reveals Ubx2 as a key regulator lipid membrane biosynthesis.
Resumo:
Cells exhibit a diverse repertoire of dynamic behaviors. These dynamic functions are implemented by circuits of interacting biomolecules. Although these regulatory networks function deterministically by executing specific programs in response to extracellular signals, molecular interactions are inherently governed by stochastic fluctuations. This molecular noise can manifest as cell-to-cell phenotypic heterogeneity in a well-mixed environment. Single-cell variability may seem like a design flaw but the coexistence of diverse phenotypes in an isogenic population of cells can also serve a biological function by increasing the probability of survival of individual cells upon an abrupt change in environmental conditions. Decades of extensive molecular and biochemical characterization have revealed the connectivity and mechanisms that constitute regulatory networks. We are now confronted with the challenge of integrating this information to link the structure of these circuits to systems-level properties such as cellular decision making. To investigate cellular decision-making, we used the well studied galactose gene-regulatory network in \textit{Saccharomyces cerevisiae}. We analyzed the mechanism and dynamics of the coexistence of two stable on and off states for pathway activity. We demonstrate that this bimodality in the pathway activity originates from two positive feedback loops that trigger bistability in the network. By measuring the dynamics of single-cells in a mixed sugar environment, we observe that the bimodality in gene expression is a transient phenomenon. Our experiments indicate that early pathway activation in a cohort of cells prior to galactose metabolism can accelerate galactose consumption and provide a transient increase in growth rate. Together these results provide important insights into strategies implemented by cells that may have been evolutionary advantageous in competitive environments.
Resumo:
DNA possesses the curious ability to conduct charge longitudinally through the π-stacked base pairs that reside within the interior of the double helix. The rate of charge transport (CT) through DNA has a shallow distance dependence. DNA CT can occur over at least 34 nm, a very long molecular distance. Lastly, DNA CT is exquisitely sensitive to disruptions, such as DNA damage, that affect the dynamics of base-pair stacking. Many DNA repair and DNA-processing enzymes are being found to contain 4Fe-4S clusters. These co-factors have been found in glycosylases, helicases, helicase-nucleases, and even enzymes such as DNA polymerase, RNA polymerase, and primase across the phylogeny. The role of these clusters in these enzymes has remained elusive. Generally, iron-sulfur clusters serve redox roles in nature since, formally, the cluster can exist in multiple oxidation states that can be accessed within a biological context. Taken together, these facts were used as a foundation for the hypothesis that DNA-binding proteins with 4Fe-4S clusters utilize DNA-mediated CT as a means to signal one another to scan the genome as a first step in locating the subtle damage that occurs within a sea of undamaged bases within cells.
Herein we describe a role for 4Fe-4S clusters in DNA-mediated charge transport signaling among EndoIII, MutY, and DinG, which are from distinct repair pathways in E. coli. The DinG helicase is an ATP-dependent helicase that contains a 4Fe-4S cluster. To study the DNA-bound redox properties of DinG, DNA-modified electrochemistry was used to show that the 4Fe-4S cluster of DNA-bound DinG is redox-active at cellular potentials, and shares the 80 mV vs. NHE redox potential of EndoIII and MutY. ATP hydrolysis by DinG increases the DNA-mediated redox signal observed electrochemically, likely reflecting better coupling of the 4Fe-4S cluster to DNA while DinG unwinds DNA, which could have interesting biological implications. Atomic force microscopy experiments demonstrate that DinG and EndoIII cooperate at long range using DNA charge transport to redistribute to regions of DNA damage. Genetics experiments, moreover, reveal that this DNA-mediated signaling among proteins also occurs within the cell and, remarkably, is required for cellular viability under conditions of stress. Knocking out DinG in CC104 cells leads to a decrease in MutY activity that is rescued by EndoIII D138A, but not EndoIII Y82A. DinG, thus, appears to help MutY find its substrate using DNA-mediated CT, but do MutY or EndoIII aid DinG in a similar way? The InvA strain of bacteria was used to observe DinG activity, since DinG activity is required within InvA to maintain normal growth. Silencing the gene encoding EndoIII in InvA results in a significant growth defect that is rescued by the overexpression of RNAseH, a protein that dismantles the substrate of DinG, R-loops. This establishes signaling between DinG and EndoIII. Furthermore, rescue of this growth defect by the expression of EndoIII D138A, the catalytically inactive but CT-proficient mutant of EndoIII, is also observed, but expression of EndoIII Y82A, which is CT-deficient but enzymatically active, does not rescue growth. These results provide strong evidence that DinG and EndoIII utilize DNA-mediated signaling to process DNA damage. This work thus expands the scope of DNA-mediated signaling within the cell, as it indicates that DNA-mediated signaling facilitates the activities of DNA repair enzymes across the genome, even for proteins from distinct repair pathways.
In separate work presented here, it is shown that the UvrC protein from E. coli contains a hitherto undiscovered 4Fe-4S cluster. A broad shoulder at 410 nm, characteristic of 4Fe-4S clusters, is observed in the UV-visible absorbance spectrum of UvrC. Electron paramagnetic resonance spectroscopy of UvrC incubated with sodium dithionite, reveals a spectrum with the signature features of a reduced, [4Fe-4S]+1, cluster. DNA-modified electrodes were used to show that UvrC has the same DNA-bound redox potential, of ~80 mV vs. NHE, as EndoIII, DinG, and MutY. Again, this means that these proteins are capable of performing inter-protein electron transfer reactions. Does UvrC use DNA-mediated signaling to facilitate the repair of its substrates?
UvrC is part of the nucleotide excision repair (NER) pathway in E. coli and is the protein within the pathway that performs the chemistry required to repair bulky DNA lesions, such as cyclopyrimidine dimers, that form as a product of UV irradiation. We tested if UvrC utilizes DNA-mediated signaling to facilitate the efficient repair of UV-induced DNA damage products by helping UvrC locate DNA damage. The UV sensitivity of E. coli cells lacking DinG, a putative signaling partner of UvrC, was examined. Knocking out DinG in E. coli leads to a sensitivity of the cells to UV irradiation. A 5-10 fold reduction in the amount of cells that survive after irradiation with 90 J/m2 of UV light is observed. This is consistent with the hypothesis that UvrC and DinG are signaling partners, but is this signaling due to DNA-mediated CT? Complementing the knockout cells with EndoIII D138A, which can also serve as a DNA CT signaling partner, rescues cells lacking DinG from UV irradiation, while complementing the cells with EndoIII Y82A shows no rescue of viability. These results indicate that there is cross-talk between the NER pathway and DinG via DNA-mediated signaling. Perhaps more importantly, this work also establishes that DinG, EndoIII, MutY, and UvrC comprise a signaling network that seems to be unified by the ability of these proteins to perform long range DNA-mediated CT signaling via their 4Fe-4S clusters.
Resumo:
Organismal development, homeostasis, and pathology are rooted in inherently probabilistic events. From gene expression to cellular differentiation, rates and likelihoods shape the form and function of biology. Processes ranging from growth to cancer homeostasis to reprogramming of stem cells all require transitions between distinct phenotypic states, and these occur at defined rates. Therefore, measuring the fidelity and dynamics with which such transitions occur is central to understanding natural biological phenomena and is critical for therapeutic interventions.
While these processes may produce robust population-level behaviors, decisions are made by individual cells. In certain circumstances, these minuscule computing units effectively roll dice to determine their fate. And while the 'omics' era has provided vast amounts of data on what these populations are doing en masse, the behaviors of the underlying units of these processes get washed out in averages.
Therefore, in order to understand the behavior of a sample of cells, it is critical to reveal how its underlying components, or mixture of cells in distinct states, each contribute to the overall phenotype. As such, we must first define what states exist in the population, determine what controls the stability of these states, and measure in high dimensionality the dynamics with which these cells transition between states.
To address a specific example of this general problem, we investigate the heterogeneity and dynamics of mouse embryonic stem cells (mESCs). While a number of reports have identified particular genes in ES cells that switch between 'high' and 'low' metastable expression states in culture, it remains unclear how levels of many of these regulators combine to form states in transcriptional space. Using a method called single molecule mRNA fluorescent in situ hybridization (smFISH), we quantitatively measure and fit distributions of core pluripotency regulators in single cells, identifying a wide range of variabilities between genes, but each explained by a simple model of bursty transcription. From this data, we also observed that strongly bimodal genes appear to be co-expressed, effectively limiting the occupancy of transcriptional space to two primary states across genes studied here. However, these states also appear punctuated by the conditional expression of the most highly variable genes, potentially defining smaller substates of pluripotency.
Having defined the transcriptional states, we next asked what might control their stability or persistence. Surprisingly, we found that DNA methylation, a mark normally associated with irreversible developmental progression, was itself differentially regulated between these two primary states. Furthermore, both acute or chronic inhibition of DNA methyltransferase activity led to reduced heterogeneity among the population, suggesting that metastability can be modulated by this strong epigenetic mark.
Finally, because understanding the dynamics of state transitions is fundamental to a variety of biological problems, we sought to develop a high-throughput method for the identification of cellular trajectories without the need for cell-line engineering. We achieved this by combining cell-lineage information gathered from time-lapse microscopy with endpoint smFISH for measurements of final expression states. Applying a simple mathematical framework to these lineage-tree associated expression states enables the inference of dynamic transitions. We apply our novel approach in order to infer temporal sequences of events, quantitative switching rates, and network topology among a set of ESC states.
Taken together, we identify distinct expression states in ES cells, gain fundamental insight into how a strong epigenetic modifier enforces the stability of these states, and develop and apply a new method for the identification of cellular trajectories using scalable in situ readouts of cellular state.