Characterizing Mutational Signatures in Human Cancer Cell Lines Reveals Episodic APOBEC Mutagenesis

1. Download high-res image (231KB)
2. Download full-size image

     

Low membrane fluidity triggers lipid phase separation and protein segregation in living bacteria

All living organisms adapt their membrane lipid composition in response to changes in their environment or diet. These conserved membrane‐adaptive processes have been studied extensively. However, key concepts of membrane biology linked to regulation of lipid composition including homeoviscous adaptation maintaining stable levels of membrane fluidity, and gel‐fluid phase separation resulting in domain formation, heavily rely upon in vitro studies with model membranes or lipid extracts. Using the bacterial model organisms Escherichia coli and Bacillus subtilis, we now show that inadequate in vivo membrane fluidity interferes with essential complex cellular processes including cytokinesis, envelope expansion, chromosome replication/segregation and maintenance of membrane potential. Furthermore, we demonstrate that very low membrane fluidity is indeed capable of triggering large‐scale lipid phase separation and protein segregation in intact, protein‐crowded membranes of living cells; a process that coincides with the minimal level of fluidity capable of supporting growth. Importantly, the in vivo lipid phase separation is not associated with a breakdown of the membrane diffusion barrier function, thus explaining why the phase separation process induced by low fluidity is biologically reversible.     

New method for the resolution of the enantiomers of 5,6-Dihydroxy-2-Methyl-Aminotetralin by selective derivatization and HPLC analysis: Application to biological fluids

A new chiral derivatization procedure for the HPLC resolution of chiral catecholamines and structurally related compounds is described. The homochiral reagent, (+)-(R)-1-phenylethyl isocyanate (RPEIC), was added to separate and quantitate the enantiomers of rac-5,6-dihydroxy-2-methyl-aminotetralin, the main metabolite of rac-5,6-diisobutyryl-2-methyl-aminotetralin, a potent dopamine agonist, by reversed-phase HLPC analysis. To avoid catecholamine degradation in the basic reaction medium and to obtain the selective and quantitative derivatization of the amino group of the compound, the reversible complex formation between diphenylborinic acid (DPBA) and the catechol group, in alkaline medium, was performed before homochiral isocyanate addition. The RPEIC derivatization was completed in 30 min and then the DPBA complex was dissociated by adding dilute acid. The structure of intermediates and urea derivatives was confirmed by mass spectrometry. The use of an electrochemical detector, operating in redox mode, allowed HPLC quantitation of enantiomers at the nanogram level in plasma and urine. The derivatization procedure is also suitable for other catecholamine-related compounds. © 1996 Wiley-Liss, Inc.     

Rare and localized events stabilize microbial community composition and patterns of spatial self-organization in a fluctuating environment

Spatial self-organization is a hallmark of surface-associated microbial communities that is governed by local environmental conditions and further modified by interspecific interactions. Here, we hypothesize that spatial patterns of microbial cell-types can stabilize the composition of cross-feeding microbial communities under fluctuating environmental conditions. We tested this hypothesis by studying the growth and spatial self-organization of microbial co-cultures consisting of two metabolically interacting strains of the bacterium Pseudomonas stutzeri. We inoculated the co-cultures onto agar surfaces and allowed them to expand (i.e. range expansion) while fluctuating environmental conditions that alter the dependency between the two strains. We alternated between anoxic conditions that induce a mutualistic interaction and oxic conditions that induce a competitive interaction. We observed co-occurrence of both strains in rare and highly localized clusters (referred to as “spatial jackpot events”) that persist during environmental fluctuations. To resolve the underlying mechanisms for the emergence of spatial jackpot events, we used a mechanistic agent-based mathematical model that resolves growth and dispersal at the scale relevant to individual cells. While co-culture composition varied with the strength of the mutualistic interaction and across environmental fluctuations, the model provides insights into the formation of spatially resolved substrate landscapes with localized niches that support the co-occurrence of the two strains and secure co-culture function. This study highlights that in addition to spatial patterns that emerge in response to environmental fluctuations, localized spatial jackpot events ensure persistence of strains across dynamic conditions.Subject terms: Microbial ecology, Biofilms     

Inclusion of maintenance energy improves the intracellular flux predictions of CHO

Chinese hamster ovary (CHO) cells are the leading platform for the production of biopharmaceuticals with human-like glycosylation. The standard practice for cell line generation relies on trial and error approaches such as adaptive evolution and high-throughput screening, which typically take several months. Metabolic modeling could aid in designing better producer cell lines and thus shorten development times. The genome-scale metabolic model (GSMM) of CHO can accurately predict growth rates. However, in order to predict rational engineering strategies it also needs to accurately predict intracellular fluxes. In this work we evaluated the agreement between the fluxes predicted by parsimonious flux balance analysis (pFBA) using the CHO GSMM and a wide range of ¹³C metabolic flux data from literature. While glycolytic fluxes were predicted relatively well, the fluxes of tricarboxylic acid (TCA) cycle were vastly underestimated due to too low energy demand. Inclusion of computationally estimated maintenance energy significantly improved the overall accuracy of intracellular flux predictions. Maintenance energy was therefore determined experimentally by running continuous cultures at different growth rates and evaluating their respective energy consumption. The experimentally and computationally determined maintenance energy were in good agreement. Additionally, we compared alternative objective functions (minimization of uptake rates of seven nonessential metabolites) to the biomass objective. While the predictions of the uptake rates were quite inaccurate for most objectives, the predictions of the intracellular fluxes were comparable to the biomass objective function.     

Estimating the number of clusters in multivariate data by self-organizing maps

Determining the structure of data without prior knowledge of the number of clusters or any information about their composition is a problem of interest in many fields, such as image analysis, astrophysics, biology, etc. Partitioning a set of n patterns in a p-dimensional feature space must be done such that those in a given cluster are more similar to each other than the rest. As there are approximately Kn/K! possible ways of partitioning the patterns among K clusters, finding the best solution is very hard when n is large. The search space is increased when we have no a priori number of partitions. Although the self-organizing feature map (SOM) can be used to visualize clusters, the automation of knowledge discovery by SOM is a difficult task. This paper proposes region-based image processing methods to post-processing the U-matrix obtained after the unsupervised learning performed by SOM. Mathematical morphology is applied to identify regions of neurons that are similar. The number of regions and their labels are automatically found and they are related to the number of clusters in a multivariate data set. New data can be classified by labeling it according to the best match neuron. Simulations using data sets drawn from finite mixtures of p-variate normal densities are presented as well as related advantages and drawbacks of the method.     

Thioredoxin can influence gene expression by affecting gyrase activity

The expression of many genes of facultatively photosynthetic bacteria of the genus Rhodobacter is controlled by the oxygen tension. Among these are the genes of the puf and puc operons, which encode proteins of the photosynthetic apparatus. Previous results revealed that thioredoxins are involved in the regulated expression of these operons, but it remained unsolved as to the mechanisms by which thioredoxins affect puf and puc expression. Here we show that reduced TrxA of Rhodobacter capsulatus and Rhodobacter sphaeroides and oxidized TrxC of R.capsulatus interact with DNA gyrase and alter its DNA supercoiling activity. While TrxA enhances supercoiling, TrxC exerts a negative effect on this activity. Furthermore, inhibition of gyrase activity strongly reduces puf and puc expression. Our results reveal a new signaling pathway by which oxygen can affect the expression of bacterial genes.