5,942 research outputs found
Simulations reveal that different responses to cell crowding determine the expansion of p53 and Notch mutant clones in squamous epithelia.
Funder: MRC Cancer unitFunder: Clare CollegeDuring ageing, normal epithelial tissues progressively accumulate clones carrying mutations that increase mutant cell fitness above that of wild-type cells. Such mutants spread widely through the tissues, yet despite this cellular homeostasis and functional integrity of the epithelia are maintained. Two of the genes most commonly mutated in human skin and oesophagus are p53 and Notch1, both of which are also recurrently mutated in cancers of these tissues. From observations taken in human and mouse epithelia, we find that clones carrying p53 and Notch pathway mutations have different clone dynamics which can be explained by their different responses to local cell crowding. p53 mutant clone growth in mouse epidermis approximates a logistic curve, but feedbacks responding to local crowding are required to maintain tissue homeostasis. We go on to show that the observed ability of Notch pathway mutant cells to displace the wild-type population in the mouse oesophageal epithelium reflects a local density feedback that affects both mutant and wild-type cells equally. We then show how these distinct feedbacks are consistent with the distribution of mutations observed in human datasets and are suggestive of a putative mechanism to constrain these cancer-associated mutants
Big Bang nucleosynthesis as a probe of new physics
The Big Bang Nucleosynthesis (BBN) model is a cornerstone for the
understanding of the evolution of the early universe, making seminal
predictions that are in outstanding agreement with the present observation of
light element abundances in the universe. Perhaps, the only remaining issue to
be solved by theory is the so-called "lithium abundance problem". Dedicated
experimental efforts to measure the relevant nuclear cross sections used as
input of the model have lead to an increased level of accuracy in the
prediction of the light element primordial abundances. The rise of indirect
experimental techniques during the preceding few decades has permitted the
access of reaction information beyond the limitations of direct measurements.
New theoretical developments have also opened a fertile ground for tests of
physics beyond the standard model of atomic, nuclear, statistics, and particle
physics. We review the latest contributions of our group for possible solutions
of the lithium problem.Comment: 9 pages, 7 figures, version accepted for publication. Refs. 69 and 70
added upon reques
Heterogeneity of the cancer cell line metabolic landscape
The unravelling of the complexity of cellular metabolism is in its infancy. Cancer-associated genetic alterations may result in changes to cellular metabolism that aid in understanding phenotypic changes, reveal detectable metabolic signatures, or elucidate vulnerabilities to particular drugs. To understand cancer-associated metabolic transformation, we performed untargeted metabolite analysis of 173 different cancer cell lines from 11 different tissues under constant conditions for 1,099 different species using mass spectrometry (MS). We correlate known cancer-associated mutations and gene expression programs with metabolic signatures, generating novel associations of known metabolic pathways with known cancer drivers. We show that metabolic activity correlates with drug sensitivity and use metabolic activity to predict drug response and synergy. Finally, we study the metabolic heterogeneity of cancer mutations across tissues, and find that genes exhibit a range of context specific, and more general metabolic control
Sidekick for membrane simulations: automated ensemble molecular dynamics simulations of transmembrane helices
The interactions of transmembrane (TM) α-
helices with the phospholipid membrane and with one another
are central to understanding the structure and stability of
integral membrane proteins. These interactions may be
analyzed via coarse grained molecular dynamics (CGMD)
simulations. To obtain statistically meaningful analysis of TM
helix interactions, large (N ca. 100) ensembles of CGMD
simulations are needed. To facilitate the running and analysis
of such ensembles of simulations, we have developed Sidekick,
an automated pipeline software for performing high
throughput CGMD simulations of α-helical peptides in lipid
bilayer membranes. Through an end-to-end approach, which
takes as input a helix sequence and outputs analytical metrics derived from CGMD simulations, we are able to predict the
orientation and likelihood of insertion into a lipid bilayer of a given helix of a family of helix sequences. We illustrate this software
via analyses of insertion into a membrane of short hydrophobic TM helices containing a single cationic arginine residue
positioned at different positions along the length of the helix. From analyses of these ensembles of simulations, we estimate
apparent energy barriers to insertion which are comparable to experimentally determined values. In a second application, we use
CGMD simulations to examine the self-assembly of dimers of TM helices from the ErbB1 receptor tyrosine kinase and analyze
the numbers of simulation repeats necessary to obtain convergence of simple descriptors of the mode of packing of the two
helices within a dimer. Our approach offers a proof-of-principle platform for the further employment of automation in large
ensemble CGMD simulations of membrane proteins
- …