Forward-in-time simulation of chromosomal rearrangements: The invisible backbone that sustains long-term adaptation.

While chromosomal rearrangements are ubiquitous in all domains of life, very little is known about their evolutionary significance, mostly because, apart from a few specifically studied and well-documented mechanisms (interaction with recombination, gene duplication, etc.), very few models take them into account. As a consequence, we lack a general theory to account for their direct and indirect contributions to evolution. Here, we propose Aevol, a forward-in-time simulation platform specifically dedicated to unravelling the evolutionary significance of chromosomal rearrangements (CR) compared to local mutations (LM). Using the platform, we evolve populations of organisms in four conditions characterized by an increasing diversity of mutational operators-from substitutions alone to a mix of substitutions, InDels and CR-but with a constant global mutational rate. Despite being almost invisible in the phylogeny owing to the scarcity of their fixation in the lineages, we show that CR make a decisive contribution to the evolutionary dynamics by comparing the outcome in these four conditions. As expected, chromosomal rearrangements allow fast expansion of the gene repertoire through gene duplication, but they also reduce the effect of diminishing-returns epistasis, hence sustaining adaptation on the long-run. At last, we show that chromosomal rearrangements tightly regulate the size of the genome through indirect selection for reproductive robustness. Overall, these results confirm the need to improve our theoretical understanding of the contribution of chromosomal rearrangements to evolution and show that dedicated platforms like Aevol can efficiently contribute to this agenda.

Obesity and hyperinsulinemia drive adipocytes to activate a cell cycle program and senesce.

Obesity is considered an important factor for many chronic diseases, including diabetes, cardiovascular disease and cancer. The expansion of adipose tissue in obesity is due to an increase in both adipocyte progenitor differentiation and mature adipocyte cell size. Adipocytes, however, are thought to be unable to divide or enter the cell cycle. We demonstrate that mature human adipocytes unexpectedly display a gene and protein signature indicative of an active cell cycle program. Adipocyte cell cycle progression associates with obesity and hyperinsulinemia, with a concomitant increase in cell size, nuclear size and nuclear DNA content. Chronic hyperinsulinemia in vitro or in humans, however, is associated with subsequent cell cycle exit, leading to a premature senescent transcriptomic and secretory profile in adipocytes. Premature senescence is rapidly becoming recognized as an important mediator of stress-induced tissue dysfunction. By demonstrating that adipocytes can activate a cell cycle program, we define a mechanism whereby mature human adipocytes senesce. We further show that by targeting the adipocyte cell cycle program using metformin, it is possible to influence adipocyte senescence and obesity-associated adipose tissue inflammation.

Rapeseed Lecithin Increases Lymphatic Lipid Output and α-Linolenic Acid Bioavailability in Rats.

BACKGROUND: Soybean lecithin, a plant-based emulsifier widely used in food, is capable of modulating postprandial lipid metabolism. With arising concerns of sustainability, alternative sources of vegetal lecithin are urgently needed, and their metabolic effects must be characterized. OBJECTIVES: We evaluated the impact of increasing doses of rapeseed lecithin (RL), rich in essential α-linolenic acid (ALA), on postprandial lipid metabolism and ALA bioavailability in lymph-cannulated rats. METHODS: Male Wistar rats (8 weeks old) undergoing a mesenteric lymph duct cannulation were intragastrically administered 1 g of an oil mixture containing 4% ALA and 0, 1, 3, 10, or 30% RL (5 groups). Lymph fractions were collected for 6 h. Lymph lipids and chylomicrons (CMs) were characterized. The expression of genes implicated in intestinal lipid metabolism was determined in the duodenum at 6 h. Data was analyzed using either sigmoidal or linear mixed-effects models, or one-way ANOVA, where appropriate. RESULTS: RL dose-dependently increased the lymphatic recovery (AUC) of total lipids (1100 µg/mL·h per additional RL%; P = 0.010) and ALA (50 µg/mL·h per additional RL%; P = 0.0076). RL induced a faster appearance of ALA in lymph, as evidenced by the exponential decrease of the rate of appearance of ALA with RL (R2 = 0.26; P = 0.0064). Although the number of CMs was unaffected by RL, CM diameter was increased in the 30%-RL group, compared to the control group (0% RL), by 86% at 3-4 h (P = 0.065) and by 81% at 4-6 h (P = 0.0002) following administration. This increase was positively correlated with the duodenal mRNA expression of microsomal triglyceride transfer protein (Mttp; ρ= 0.63; P = 0.0052). The expression of Mttp and secretion-associated, ras-related GTPase 1 gene homolog B (Sar1b, CM secretion), carnitine palmitoyltransferase IA (Cpt1a) and acyl-coenzyme A oxidase 1 (Acox1, beta-oxidation), and fatty acid desaturase 2 (Fads2, bioconversion of ALA into long-chain n-3 PUFAs) were, respectively, 49%, 29%, 74%, 48%, and 55% higher in the 30%-RL group vs. the control group (P < 0.05). CONCLUSIONS: In rats, RL enhanced lymphatic lipid output, as well as the rate of appearance of ALA, which may promote its subsequent bioavailability and metabolic fate.

Phenotypic noise and the cost of complexity.

Experimental studies demonstrate the existence of phenotypic diversity despite constant genotype and environment. Theoretical models based on a single phenotypic character predict that during an adaptation event, phenotypic noise should be positively selected far from the fitness optimum because it increases the fitness of the genotype, and then be selected against when the population reaches the optimum. It is suggested that because of this fitness gain, phenotypic noise should promote adaptive evolution. However, it is unclear how the selective advantage of phenotypic noise is linked to the rate of evolution, and whether any advantage would hold for more realistic, multidimensional phenotypes. Indeed, complex organisms suffer a cost of complexity, where beneficial mutations become rarer as the number of phenotypic characters increases. Using a quantitative genetics approach, we first show that for a one-dimensional phenotype, phenotypic noise promotes adaptive evolution on plateaus of positive fitness, independently from the direct selective advantage on fitness. Second, we show that for multidimensional phenotypes, phenotypic noise evolves to a low-dimensional configuration, with elevated noise in the direction of the fitness optimum. Such a dimensionality reduction of the phenotypic noise promotes adaptive evolution and numerical simulations show that it reduces the cost of complexity.

Human milk pasteurisation reduces pre-lipolysis but not digestive lipolysis and moderately decreases intestinal lipid uptake in a combination of preterm infant in vitro models.

Donor human milk, pasteurised for safety reasons, is the first alternative for feeding preterm infants when mothers' own milk is unavailable. Breastmilk pasteurisation impact on lipid digestion and absorption was evaluated by a static in vitro digestion model for preterm infants coupled with intestinal absorption using Caco-2/TC7 cells. Lipid absorption was quantified by digital image analysis of lipid droplets, by measurement of basolateral triglyceride concentration and by analysing the expression of major genes involved. After in vitro digestion, lipolysis extent was 13% lower in pasteurised human milk (PHM) than in raw human milk (RHM). In Caco-2/TC7 cells, the number of lipid droplets was identical for both milk types, while the mean droplet area was 17% smaller with PHM. Altogether, pasteurisation decreased the pre-lipolysis of human milk. This initial difference in free fatty acid amount was only partially buffered by the subsequent processes of in vitro digestion and cellular lipid absorption.

Postprandial Endotoxin Transporters LBP and sCD14 Differ in Obese vs. Overweight and Normal Weight Men during Fat-Rich Meal Digestion.

Circulating levels of lipopolysaccharide-binding protein (LBP) and soluble cluster of differentiation 14 (sCD14) are recognized as clinical markers of endotoxemia. In obese men, postprandial endotoxemia is modulated by the amount of fat ingested, being higher compared to normal-weight (NW) subjects. Relative variations of LBP/sCD14 ratio in response to overfeeding are also considered important in the inflammation set-up, as measured through IL-6 concentration. We tested the hypothesis that postprandial LBP and sCD14 circulating concentrations differed in obese vs. overweight and NW men after a fat-rich meal. We thus analyzed the postprandial kinetics of LBP and sCD14 in the context of two clinical trials involving postprandial tests in normal-, over-weight and obese men. In the first clinical trial eight NW and 8 obese men ingested breakfasts containing 10 vs. 40 g of fat. In the second clinical trial, 18 healthy men were overfed during 8 weeks. sCD14, LBP and Il-6 were measured in all subjects during 5 h after test meal. Obese men presented a higher fasting and postprandial LBP concentration in plasma than NW men regardless of fat load, while postprandial sCD14 was similar in both groups. Irrespective of the overfeeding treatment, we observed postprandial increase of sCD14 and decrease of LBP before and after OF. In obese individuals receiving a 10 g fat load, whereas IL-6 increased 5h after meal, LBP and sCD14 did not increase. No direct association between the postprandial kinetics of endotoxemia markers sCD14 and LBP and of inflammation in obese men was observed in this study.

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities.

Evolution provides a creative fount of complex and subtle adaptations that often surprise the scientists who discover them. However, the creativity of evolution is not limited to the natural world: Artificial organisms evolving in computational environments have also elicited surprise and wonder from the researchers studying them. The process of evolution is an algorithmic process that transcends the substrate in which it occurs. Indeed, many researchers in the field of digital evolution can provide examples of how their evolving algorithms and organisms have creatively subverted their expectations or intentions, exposed unrecognized bugs in their code, produced unexpectedly adaptations, or engaged in behaviors and outcomes, uncannily convergent with ones found in nature. Such stories routinely reveal surprise and creativity by evolution in these digital worlds, but they rarely fit into the standard scientific narrative. Instead they are often treated as mere obstacles to be overcome, rather than results that warrant study in their own right. Bugs are fixed, experiments are refocused, and one-off surprises are collapsed into a single data point. The stories themselves are traded among researchers through oral tradition, but that mode of information transmission is inefficient and prone to error and outright loss. Moreover, the fact that these stories tend to be shared only among practitioners means that many natural scientists do not realize how interesting and lifelike digital organisms are and how natural their evolution can be. To our knowledge, no collection of such anecdotes has been published before. This article is the crowd-sourced product of researchers in the fields of artificial life and evolutionary computation who have provided first-hand accounts of such cases. It thus serves as a written, fact-checked collection of scientifically important and even entertaining stories. In doing so we also present here substantial evidence that the existence and importance of evolutionary surprises extends beyond the natural world, and may indeed be a universal property of all complex evolving systems.

Homogeneous triacylglycerol tracers have an impact on the thermal and structural properties of dietary fat and its lipolysis rate under simulated physiological conditions.

Dietary fats are present in the diet under different types of structures, such as spread vs emulsions (notably in processed foods and enteral formula), and interest is growing regarding their digestion and intestinal absorption. In clinical trials, there is often a need to add stable isotope-labeled triacylglycerols (TAGs) as tracers to the ingested fat in order to track its intestinal absorption and further metabolic fate. Because most TAG tracers contain saturated fatty acids, they may modify the physicochemical properties of the ingested labeled fat and thereby its digestion. However, the actual impact of tracer addition on fat crystalline properties and lipolysis by digestive lipases still deserves to be explored. In this context, we monitored the thermal and polymorphic behavior of anhydrous milk fat (AMF) enriched in homogeneous TAGs tracers and further compared it with the native AMF using differential scanning calorimetry and power X-ray diffraction. As tracers, we used a mixture of tripalmitin, triolein and tricaprylin at 2 different concentrations (1.5 and 5.7 wt%, which have been used in clinical trials). The addition of TAG tracers modified the AMF melting profile, especially at the highest tested concentration (5.7 wt%). Both AMF and AMF enriched with 1.5 wt% tracers were completely melted around 37 °C, i.e. close to the body temperature, while the AMF enriched with 5.7 wt% tracers remained partially crystallized at this temperature. Similar trends were observed in both bulk and emulsified systems. Moreover, the kinetics of AMF polymorphic transformation was modified in the presence of tracers. While only ß' form was observed in the native AMF, the ß-form was clearly detected in the AMF containing 5.7 wt% tracers. We further tested the impact of tracers on the lipolysis of AMF in bulk using a static in vitro model of duodenal digestion. Lipolysis of AMF enriched with 5.7 wt% tracers was delayed compared with that of AMF and AMF enriched with 1.5 wt% tracers. Therefore, low amounts of TAG tracers including tripalmitin do not have a high impact on fat digestion, but one has to be cautious when using higher amounts of these tracers.

In vitro oxidized HDL and HDL from type 2 diabetes patients have reduced ability to efflux oxysterols from THP-1 macrophages.

Oxidized LDL (OxLDL) that are enriched in products of lipid peroxidation including oxysterols have been shown to induce cellular oxidative stress and cytotoxicity therefore accelerating atheroma plaque formation. Upon oxLDL exposure of THP-1 macrophages, intracellular oxidation of LDL derived-cholesterol as well as endogenous cholesterol was increased. The oxysterols intracellularly produced were efficiently exported to HDL whereas apolipoprotein A1 was inefficient. These findings prompted us to investigate the consequences of modification of HDL by oxidation and glycation as observed in type 2 diabetes with respect to oxysterol and cholesterol efflux. We show that efflux of oxysterols was significantly impaired after in vitro oxidation and glycoxidation of HDL whereas glycation alone had no impact. Cholesterol efflux was only slightly decreased by oxHDL or glycoxidized HDL and not changed with glycated HDL. The defect of HDL towards oxysterol efflux was also observed with HDL isolated from diabetic subjects as compared to healthy controls. These findings support a deleterious cellular retention of oxysterols due to dysfunctional HDL in type 2 diabetes.

Beware batch culture: Seasonality and niche construction predicted to favor bacterial adaptive diversification.

Metabolic cross-feeding interactions between microbial strains are common in nature, and emerge during evolution experiments in the laboratory, even in homogeneous environments providing a single carbon source. In sympatry, when the environment is well-mixed, the reasons why emerging cross-feeding interactions may sometimes become stable and lead to monophyletic genotypic clusters occupying specific niches, named ecotypes, remain unclear. As an alternative to evolution experiments in the laboratory, we developed Evo2Sim, a multi-scale model of in silico experimental evolution, equipped with the whole tool case of experimental setups, competition assays, phylogenetic analysis, and, most importantly, allowing for evolvable ecological interactions. Digital organisms with an evolvable genome structure encoding an evolvable metabolic network evolved for tens of thousands of generations in environments mimicking the dynamics of real controlled environments, including chemostat or batch culture providing a single limiting resource. We show here that the evolution of stable cross-feeding interactions requires seasonal batch conditions. In this case, adaptive diversification events result in two stably co-existing ecotypes, with one feeding on the primary resource and the other on by-products. We show that the regularity of serial transfers is essential for the maintenance of the polymorphism, as it allows for at least two stable seasons and thus two temporal niches. A first season is externally generated by the transfer into fresh medium, while a second one is internally generated by niche construction as the provided nutrient is replaced by secreted by-products derived from bacterial growth. In chemostat conditions, even if cross-feeding interactions emerge, they are not stable on the long-term because fitter mutants eventually invade the whole population. We also show that the long-term evolution of the two stable ecotypes leads to character displacement, at the level of the metabolic network but also of the genome structure. This difference of genome structure between both ecotypes impacts the stability of the cross-feeding interaction, when the population is propagated in chemostat conditions. This study shows the crucial role played by seasonality in temporal niche partitioning and in promoting cross-feeding subgroups into stable ecotypes, a premise to sympatric speciation.

Breaking Good: Accounting for Fragility of Genomic Regions in Rearrangement Distance Estimation.

Models of evolution by genome rearrangements are prone to two types of flaws: One is to ignore the diversity of susceptibility to breakage across genomic regions, and the other is to suppose that susceptibility values are given. Without necessarily supposing their precise localization, we call "solid" the regions that are improbably broken by rearrangements and "fragile" the regions outside solid ones. We propose a model of evolution by inversions where breakage probabilities vary across fragile regions and over time. It contains as a particular case the uniform breakage model on the nucleotidic sequence, where breakage probabilities are proportional to fragile region lengths. This is very different from the frequently used pseudouniform model where all fragile regions have the same probability to break. Estimations of rearrangement distances based on the pseudouniform model completely fail on simulations with the truly uniform model. On pairs of amniote genomes, we show that identifying coding genes with solid regions yields incoherent distance estimations, especially with the pseudouniform model, and to a lesser extent with the truly uniform model. This incoherence is solved when we coestimate the number of fragile regions with the rearrangement distance. The estimated number of fragile regions is surprisingly small, suggesting that a minority of regions are recurrently used by rearrangements. Estimations for several pairs of genomes at different divergence times are in agreement with a slowly evolvable colocalization of active genomic regions in the cell.

Reductive genome evolution at both ends of the bacterial population size spectrum.

Bacterial genomes show substantial variations in size. The smallest bacterial genomes are those of endocellular symbionts of eukaryotic hosts, which have undergone massive genome reduction and show patterns that are consistent with the degenerative processes that are predicted to occur in species with small effective population sizes. However, similar genome reduction is found in some free-living marine cyanobacteria that are characterized by extremely large populations. In this Opinion article, we discuss the different hypotheses that have been proposed to account for this reductive genome evolution at both ends of the bacterial population size spectrum.

A model for genome size evolution.

We present a model for genome size evolution that takes into account both local mutations such as small insertions and small deletions, and large chromosomal rearrangements such as duplications and large deletions. We introduce the possibility of undergoing several mutations within one generation. The model, albeit minimalist, reveals a non-trivial spontaneous dynamics of genome size: in the absence of selection, an arbitrary large part of genomes remains beneath a finite size, even for a duplication rate 2.6-fold higher than the rate of large deletions, and even if there is also a systematic bias toward small insertions compared to small deletions. Specifically, we show that the condition of existence of an asymptotic stationary distribution for genome size non-trivially depends on the rates and mean sizes of the different mutation types. We also give upper bounds for the median and other quantiles of the genome size distribution, and argue that these bounds cannot be overcome by selection. Taken together, our results show that the spontaneous dynamics of genome size naturally prevents it from growing infinitely, even in cases where intuition would suggest an infinite growth. Using quantitative numerical examples, we show that, in practice, a shrinkage bias appears very quickly in genomes undergoing mutation accumulation, even though DNA gains and losses appear to be perfectly symmetrical at first sight. We discuss this spontaneous dynamics in the light of the other evolutionary forces proposed in the literature and argue that it provides them a stability-related size limit below which they can act.

In silico experimental evolution: a tool to test evolutionary scenarios.

Comparative genomics has revealed that some species have exceptional genomes, compared to their closest relatives. For instance, some species have undergone a strong reduction of their genome with a drastic reduction of their genic repertoire. Deciphering the causes of these atypical trajectories can be very difficult because of the many phenomena that are intertwined during their evolution (e.g. changes of population size, environment structure and dynamics, selection strength, mutation rates...). Here we propose a methodology based on synthetic experiments to test the individual effect of these phenomena on a population of simulated organisms. We developed an evolutionary model--aevol--in which evolutionary conditions can be changed one at a time to test their effects on genome size and organization (e.g. coding ratio). To illustrate the proposed approach, we used aevol to test the effects of a strong reduction in the selection strength on a population of (simulated) bacteria. Our results show that this reduction of selection strength leads to a genome reduction of ~35% with a slight loss of coding sequences (~15% of the genes are lost--mainly those for which the contribution to fitness is the lowest). More surprisingly, under a low selection strength, genomes undergo a strong reduction of the noncoding compartment (~55% of the noncoding sequences being lost). These results are consistent with what is observed in reduced Prochlorococcus strains (marine cyanobacteria) when compared to close relatives.

New insights into bacterial adaptation through in vivo and in silico experimental evolution.

Microbiology research has recently undergone major developments that have led to great progress towards obtaining an integrated view of microbial cell function. Microbial genetics, high-throughput technologies and systems biology have all provided an improved understanding of the structure and function of bacterial genomes and cellular networks. However, integrated evolutionary perspectives are needed to relate the dynamics of adaptive changes to the phenotypic and genotypic landscapes of living organisms. Here, we review evolution experiments, carried out both in vivo with microorganisms and in silico with artificial organisms, that have provided insights into bacterial adaptation and emphasize the potential of bacterial regulatory networks to evolve.

The topology of the protein network influences the dynamics of gene order: from systems biology to a systemic understanding of evolution.

Abstract Systems biology invites us to consider the dynamic interactions between the components of a living cell. Here, by evolving artificial organisms whose genomes encode protein networks, we show that a coupling emerges at the evolutionary time scale between the protein network and the structure of the genome. Gene order is more stable when the protein network is more densely connected, which most likely results from a long-term selection for mutational robustness. Understanding evolving organisms thus requires a systemic approach, taking into account the functional interactions between gene products, but also the global relationships between the genome and the proteome at the evolutionary time scale.

A long-term evolutionary pressure on the amount of noncoding DNA.

A significant part of eukaryotic noncoding DNA is viewed as the passive result of mutational processes, such as the proliferation of mobile elements. However, sequences lacking an immediate utility can nonetheless play a major role in the long-term evolvability of a lineage, for instance by promoting genomic rearrangements. They could thus be subject to an indirect selection. Yet, such a long-term effect is difficult to isolate either in vivo or in vitro. Here, by performing in silico experimental evolution, we demonstrate that, under low mutation rates, the indirect selection of variability promotes the accumulation of noncoding sequences: Even in the absence of self-replicating elements and mutational bias, noncoding sequences constituted an important fraction of the evolved genome because the indirectly selected genomes were those that were variable enough to discover beneficial mutations. On the other hand, high mutation rates lead to compact genomes, much like the viral ones, although no selective cost of genome size was applied: The indirectly selected genomes were those that were small enough for the genetic information to be reliably transmitted. Thus, the spontaneous evolution of the amount of noncoding DNA strongly depends on the mutation rate. Our results suggest the existence of an additional pressure on the amount of noncoding DNA, namely the indirect selection of an appropriate trade-off between the fidelity of the transmission of the genetic information and the exploration of the mutational neighborhood. Interestingly, this trade-off resulted robustly in the accumulation of noncoding DNA so that the best individual leaves one offspring without mutation (or only neutral ones) per generation.

Evolutionary coupling between the deleteriousness of gene mutations and the amount of non-coding sequences.

The phenotypic effects of random mutations depend on both the architecture of the genome and the gene-trait relationships. Both levels thus play a key role in the mutational variability of the phenotype, and hence in the long-term evolutionary success of the lineage. Here, by simulating the evolution of organisms with flexible genomes, we show that the need for an appropriate phenotypic variability induces a relationship between the deleteriousness of gene mutations and the quantity of non-coding sequences maintained in the genome. The more deleterious the gene mutations, the shorter the intergenic sequences. Indeed, in a shorter genome, fewer genes are affected by rearrangements (duplications, deletions, inversions, translocations) at each replication, which compensates for the higher impact of each gene mutation. This spontaneous adjustment of genome structure allows the organisms to retain the same average fitness loss per replication, despite the higher impact of single gene mutations. These results show how evolution can generate unexpected couplings between distinct organization levels.