87 research outputs found
Coding limits on the number of transcription factors
Transcription factor proteins bind specific DNA sequences to control the
expression of genes. They contain DNA binding domains which belong to several
super-families, each with a specific mechanism of DNA binding. The total number
of transcription factors encoded in a genome increases with the number of genes
in the genome. Here, we examined the number of transcription factors from each
super-family in diverse organisms.
We find that the number of transcription factors from most super-families
appears to be bounded. For example, the number of winged helix factors does not
generally exceed 300, even in very large genomes. The magnitude of the maximal
number of transcription factors from each super-family seems to correlate with
the number of DNA bases effectively recognized by the binding mechanism of that
super-family. Coding theory predicts that such upper bounds on the number of
transcription factors should exist, in order to minimize cross-binding errors
between transcription factors. This theory further predicts that factors with
similar binding sequences should tend to have similar biological effect, so
that errors based on mis-recognition are minimal. We present evidence that
transcription factors with similar binding sequences tend to regulate genes
with similar biological functions, supporting this prediction.
The present study suggests limits on the transcription factor repertoire of
cells, and suggests coding constraints that might apply more generally to the
mapping between binding sites and biological function.Comment: http://www.weizmann.ac.il/complex/tlusty/papers/BMCGenomics2006.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1590034/
http://www.biomedcentral.com/1471-2164/7/23
A Universal Mechanism Ties Genotype to Phenotype in Trinucleotide Diseases
Trinucleotide hereditary diseases such as Huntington disease and Friedreich ataxia are cureless diseases associated with inheriting an abnormally large number of DNA trinucleotide repeats in a gene. The genes associated with different diseases are unrelated and harbor a trinucleotide repeat in different functional regions; therefore, it is striking that many of these diseases have similar correlations between their genotype, namely the number of inherited repeats and age of onset and progression phenotype. These correlations remain unexplained despite more than a decade of research. Although mechanisms have been proposed for several trinucleotide diseases, none of the proposals, being disease-specific, can account for the commonalities among these diseases. Here, we propose a universal mechanism in which length-dependent somatic repeat expansion occurs during the patient's lifetime toward a pathological threshold. Our mechanism uniformly explains for the first time to our knowledge the genotype–phenotype correlations common to trinucleotide disease and is well-supported by both experimental and clinical data. In addition, mathematical analysis of the mechanism provides simple explanations to a wide range of phenomena such as the exponential decrease of the age-of-onset curve, similar onset but faster progression in patients with Huntington disease with homozygous versus heterozygous mutation, and correlation of age of onset with length of the short allele but not with the long allele in Friedreich ataxia. If our proposed universal mechanism proves to be the core component of the actual mechanisms of specific trinucleotide diseases, it would open the search for a uniform treatment for all these diseases, possibly by delaying the somatic expansion process
Amplification of multiple genomic loci from single cells isolated by laser micro-dissection of tissues
<p>Abstract</p> <p>Background</p> <p>Whole genome amplification (WGA) and laser assisted micro-dissection represent two recently developed technologies that can greatly advance biological and medical research. WGA allows the analysis of multiple genomic loci from a single genome and has been performed on single cells from cell suspensions and from enzymatically-digested tissues. Laser micro-dissection makes it possible to isolate specific single cells from heterogeneous tissues.</p> <p>Results</p> <p>Here we applied for the first time WGA on laser micro-dissected single cells from stained tissue sections, and developed a protocol for sequentially performing the two procedures. The combined procedure allows correlating the cell's genome with its natural morphology and precise anatomical position. From each cell we amplified 122 genomic and mitochondrial loci. In cells obtained from fresh tissue sections, 64.5% of alleles successfully amplified to ~700000 copies each, and mitochondrial DNA was amplified successfully in all cells. Multiplex PCR amplification and analysis of cells from pre-stored sections yielded significantly poorer results. Sequencing and capillary electrophoresis of WGA products allowed detection of slippage mutations in microsatellites (MS), and point mutations in P53.</p> <p>Conclusion</p> <p>Comprehensive genomic analysis of single cells from stained tissue sections opens new research opportunities for cell lineage and depth analyses, genome-wide mutation surveys, and other single cell assays.</p
Subgraphs and network motifs in geometric networks
Many real-world networks describe systems in which interactions decay with
the distance between nodes. Examples include systems constrained in real space
such as transportation and communication networks, as well as systems
constrained in abstract spaces such as multivariate biological or economic
datasets and models of social networks. These networks often display network
motifs: subgraphs that recur in the network much more often than in randomized
networks. To understand the origin of the network motifs in these networks, it
is important to study the subgraphs and network motifs that arise solely from
geometric constraints. To address this, we analyze geometric network models, in
which nodes are arranged on a lattice and edges are formed with a probability
that decays with the distance between nodes. We present analytical solutions
for the numbers of all 3 and 4-node subgraphs, in both directed and
non-directed geometric networks. We also analyze geometric networks with
arbitrary degree sequences, and models with a field that biases for directed
edges in one direction. Scaling rules for scaling of subgraph numbers with
system size, lattice dimension and interaction range are given. Several
invariant measures are found, such as the ratio of feedback and feed-forward
loops, which do not depend on system size, dimension or connectivity function.
We find that network motifs in many real-world networks, including social
networks and neuronal networks, are not captured solely by these geometric
models. This is in line with recent evidence that biological network motifs
were selected as basic circuit elements with defined information-processing
functions.Comment: 9 pages, 6 figure
Oscillations and variability in the p53 system
Understanding the dynamics and variability of protein circuitry requires accurate measurements in living cells as well as theoretical models. To address this, we employed one of the best-studied protein circuits in human cells, the negative feedback loop between the tumor suppressor p53 and the oncogene Mdm2. We measured the dynamics of fluorescently tagged p53 and Mdm2 over several days in individual living cells. We found that isogenic cells in the same environment behaved in highly variable ways following DNA-damaging gamma irradiation: some cells showed undamped oscillations for at least 3 days (more than 10 peaks). The amplitude of the oscillations was much more variable than the period. Sister cells continued to oscillate in a correlated way after cell division, but lost correlation after about 11 h on average. Other cells showed low-frequency fluctuations that did not resemble oscillations. We also analyzed different families of mathematical models of the system, including a novel checkpoint mechanism. The models point to the possible source of the variability in the oscillations: low-frequency noise in protein production rates, rather than noise in other parameters such as degradation rates. This study provides a view of the extensive variability of the behavior of a protein circuit in living human cells, both from cell to cell and in the same cell over time
Coarse-Graining and Self-Dissimilarity of Complex Networks
Can complex engineered and biological networks be coarse-grained into smaller
and more understandable versions in which each node represents an entire
pattern in the original network? To address this, we define coarse-graining
units (CGU) as connectivity patterns which can serve as the nodes of a
coarse-grained network, and present algorithms to detect them. We use this
approach to systematically reverse-engineer electronic circuits, forming
understandable high-level maps from incomprehensible transistor wiring: first,
a coarse-grained version in which each node is a gate made of several
transistors is established. Then, the coarse-grained network is itself
coarse-grained, resulting in a high-level blueprint in which each node is a
circuit-module made of multiple gates. We apply our approach also to a
mammalian protein-signaling network, to find a simplified coarse-grained
network with three main signaling channels that correspond to cross-interacting
MAP-kinase cascades. We find that both biological and electronic networks are
'self-dissimilar', with different network motifs found at each level. The
present approach can be used to simplify a wide variety of directed and
nondirected, natural and designed networks.Comment: 11 pages, 11 figure
Single-molecule transcript counting of stem-cell markers in the mouse intestine
available in PMC 2012 July 1.Determining the molecular identities of adult stem cells requires technologies for sensitive transcript detection in tissues. In mouse intestinal crypts, lineage-tracing studies indicated that different genes uniquely mark spatially distinct stem-cell populations, residing either at crypt bases or at position +4, but a detailed analysis of their spatial co-expression has not been feasible. Here we apply three-colour single-molecule fluorescent in situ hybridization to study a comprehensive panel of intestinal stem-cell markers during homeostasis, ageing and regeneration. We find that the expression of all markers overlaps at crypt-base cells. This co-expression includes Lgr5, Bmi1 and mTert, genes previously suggested to mark distinct stem cells. Strikingly, Dcamkl1 tuft cells, distributed throughout the crypt axis, co-express Lgr5 and other stem-cell markers that are otherwise confined to crypt bases. We also detect significant changes in the expression of some of the markers following irradiation, indicating their potential role in the regeneration process. Our approach can enable the sensitive detection of putative stem cells in other tissues and in tumours, guiding complementary functional studies to evaluate their stem-cell properties.National Institutes of Health (U.S.) (U54CA143874)National Cancer Institute (U.S.) (Physical Sciences Oncology Center at MIT (U54CA143874))National Institutes of Health (U.S.) (NIH Pioneer award (1DP1OD003936))National Cancer Institute (U.S.) (Cancer Center Support (core) grant P30-CA14051)European Molecular Biology Organization (postdoctoral fellowship)Human Frontier Science Program (Strasbourg, France)Machiah FoundationHoward Hughes Medical Institute (Gilliam fellowship
Estimating Cell Depth from Somatic Mutations
The depth of a cell of a multicellular organism is the number of cell divisions it underwent since the zygote, and knowing this basic cell property would help address fundamental problems in several areas of biology. At present, the depths of the vast majority of human and mouse cell types are unknown. Here, we show a method for estimating the depth of a cell by analyzing somatic mutations in its microsatellites, and provide to our knowledge for the first time reliable depth estimates for several cells types in mice. According to our estimates, the average depth of oocytes is 29, consistent with previous estimates. The average depth of B cells ranges from 34 to 79, linearly related to the mouse age, suggesting a rate of one cell division per day. In contrast, various types of adult stem cells underwent on average fewer cell divisions, supporting the notion that adult stem cells are relatively quiescent. Our method for depth estimation opens a window for revealing tissue turnover rates in animals, including humans, which has important implications for our knowledge of the body under physiological and pathological conditions
Invariant Distribution of Promoter Activities in Escherichia coli
Cells need to allocate their limited resources to express a wide range of genes. To understand how Escherichia coli partitions its transcriptional resources between its different promoters, we employ a robotic assay using a comprehensive reporter strain library for E. coli to measure promoter activity on a genomic scale at high-temporal resolution and accuracy. This allows continuous tracking of promoter activity as cells change their growth rate from exponential to stationary phase in different media. We find a heavy-tailed distribution of promoter activities, with promoter activities spanning several orders of magnitude. While the shape of the distribution is almost completely independent of the growth conditions, the identity of the promoters expressed at different levels does depend on them. Translation machinery genes, however, keep the same relative expression levels in the distribution across conditions, and their fractional promoter activity tracks growth rate tightly. We present a simple optimization model for resource allocation which suggests that the observed invariant distributions might maximize growth rate. These invariant features of the distribution of promoter activities may suggest design constraints that shape the allocation of transcriptional resources
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