Evidence for a Grooming Claw in a North American Adapiform Primate: Implications for Anthropoid Origins

Among fossil primates, the Eocene adapiforms have been suggested as the closest relatives of living anthropoids (monkeys, apes, and humans). Central to this argument is the form of the second pedal digit. Extant strepsirrhines and tarsiers possess a grooming claw on this digit, while most anthropoids have a nail. While controversial, the possible presence of a nail in certain European adapiforms has been considered evidence for anthropoid affinities. Skeletons preserved well enough to test this idea have been lacking for North American adapiforms. Here, we document and quantitatively analyze, for the first time, a dentally associated skeleton of Notharctus tenebrosus from the early Eocene of Wyoming that preserves the complete bones of digit II in semi-articulation. Utilizing twelve shape variables, we compare the distal phalanges of Notharctus tenebrosus to those of extant primates that bear nails (n = 21), tegulae (n = 4), and grooming claws (n = 10), and those of non-primates that bear claws (n = 7). Quantitative analyses demonstrate that Notharctus tenebrosus possessed a grooming claw with a surprisingly well-developed apical tuft on its second pedal digit. The presence of a wide apical tuft on the pedal digit II of Notharctus tenebrosus may reflect intermediate morphology between a typical grooming claw and a nail, which is consistent with the recent hypothesis that loss of a grooming claw occurred in a clade containing adapiforms (e.g. Darwinius masillae) and anthropoids. However, a cladistic analysis including newly documented morphologies and thorough representation of characters acknowledged to have states constituting strepsirrhine, haplorhine, and anthropoid synapomorphies groups Notharctus tenebrosus and Darwinius masillae with extant strepsirrhines rather than haplorhines suggesting that the form of pedal digit II reflects substantial homoplasy during the course of early primate evolution

Suppression of Plant Resistance Gene-Based Immunity by a Fungal Effector

The innate immune system of plants consists of two layers. The first layer, called basal resistance, governs recognition of conserved microbial molecules and fends off most attempted invasions. The second layer is based on Resistance (R) genes that mediate recognition of effectors, proteins secreted by pathogens to suppress or evade basal resistance. Here, we show that a plant-pathogenic fungus secretes an effector that can both trigger and suppress R gene-based immunity. This effector, Avr1, is secreted by the xylem-invading fungus Fusarium oxysporum f.sp. lycopersici (Fol) and triggers disease resistance when the host plant, tomato, carries a matching R gene (I or I-1). At the same time, Avr1 suppresses the protective effect of two other R genes, I-2 and I-3. Based on these observations, we tentatively reconstruct the evolutionary arms race that has taken place between tomato R genes and effectors of Fol. This molecular analysis has revealed a hitherto unpredicted strategy for durable disease control based on resistance gene combinations

From bit to it: How a complex metabolic network transforms information into living matter

Organisms live and die by the amount of information they acquire about their environment. The systems analysis of complex metabolic networks allows us to ask how such information translates into fitness. A metabolic network transforms nutrients into biomass. The better it uses information on available nutrient availability, the faster it will allow a cell to divide. I here use metabolic flux balance analysis to show that the accuracy I (in bits) with which a yeast cell can sense a limiting nutrient's availability relates logarithmically to fitness as indicated by biomass yield and cell division rate. For microbes like yeast, natural selection can resolve fitness differences of genetic variants smaller than 10-6, meaning that cells would need to estimate nutrient concentrations to very high accuracy (greater than 22 bits) to ensure optimal growth. I argue that such accuracies are not achievable in practice. Natural selection may thus face fundamental limitations in maximizing the information processing capacity of cells. The analysis of metabolic networks opens a door to understanding cellular biology from a quantitative, information-theoretic perspective

Single TNFα trimers mediating NF-κB activation: stochastic robustness of NF-κB signaling

Background: The NF-κB regulatory network controls innate immune response by transducing variety of pathogen-derived and cytokine stimuli into well defined single-cell gene regulatory events. Results: We analyze the network by means of the model combining a deterministic description for molecular species with large cellular concentrations with two classes of stochastic switches: cell-surface receptor activation by TNFα ligand, and IκBα and A20 genes activation by NF-κB molecules. Both stochastic switches are associated with amplification pathways capable of translating single molecular events into tens of thousands of synthesized or degraded proteins. Here, we show that at a low TNFα dose only a fraction of cells are activated, but in these activated cells the amplification mechanisms assure that the amplitude of NF-κB nuclear translocation remains above a threshold. Similarly, the lower nuclear NF-κB concentration only reduces the probability of gene activation, but does not reduce gene expression of those responding. Conclusion: These two effects provide a particular stochastic robustness in cell regulation, allowing cells to respond differently to the same stimuli, but causing their individual responses to be unequivocal. Both effects are likely to be crucial in the early immune response: Diversity in cell responses causes that the tissue defense is harder to overcome by relatively simple programs coded in viruses and other pathogens. The more focused single-cell responses help cells to choose their individual fates such as apoptosis or proliferation. The model supports the hypothesis that binding of single TNFα ligands is sufficient to induce massive NF-κB translocation and activation of NF-κB dependent genes. © 2007 Lipniacki et al; licensee BioMed Central Ltd

A first genome assembly of the barley fungal pathogen Pyrenophora teres f. teres

Background: Pyrenophora teres f. teres is a necrotrophic fungal pathogen and the cause of one of barley’s most important diseases, net form of net blotch. Here we report the first genome assembly for this species based solely on short Solexa sequencing reads of isolate 0-1. The assembly was validated by comparison to BAC sequences, ESTs, orthologous genes and by PCR, and complemented by cytogenetic karyotyping and the first genome-wide genetic map for P. teres f. teres. Results: The total assembly was 41.95 Mbp and contains 11,799 gene models of 50 amino acids or more. Comparison against two sequenced BACs showed that complex regions with a high GC content assembled effectively. Electrophoretic karyotyping showed distinct chromosomal polymorphisms between isolates 0-1 and 15A, and cytological karyotyping confirmed the presence of at least nine chromosomes. The genetic map spans 2477.7 cM and is composed of 243 markers in 25 linkage groups, and incorporates SSR markers developed from the assembly. Among predicted genes, non-ribosomal peptide synthetases and efflux pumps in particular appear to have undergone a P. teres f. teres-specific expansion of non-orthologous gene families. Conclusions: This study demonstrates that paired-end Solexa sequencing can successfully capture coding regions of a filamentous fungal genome. The assembly contains a plethora of predicted genes that have been implicated in a necrotrophic lifestyle and pathogenicity and presents a significant resource for examining the bases for P. teres f. teres pathogenicity

Multiple Translocation of the AVR-Pita Effector Gene among Chromosomes of the Rice Blast Fungus Magnaporthe oryzae and Related Species

Magnaporthe oryzae is the causal agent of rice blast disease, a devastating problem worldwide. This fungus has caused breakdown of resistance conferred by newly developed commercial cultivars. To address how the rice blast fungus adapts itself to new resistance genes so quickly, we examined chromosomal locations of AVR-Pita, a subtelomeric gene family corresponding to the Pita resistance gene, in various isolates of M. oryzae (including wheat and millet pathogens) and its related species. We found that AVR-Pita (AVR-Pita1 and AVR-Pita2) is highly variable in its genome location, occurring in chromosomes 1, 3, 4, 5, 6, 7, and supernumerary chromosomes, particularly in rice-infecting isolates. When expressed in M. oryzae, most of the AVR-Pita homologs could elicit Pita-mediated resistance, even those from non-rice isolates. AVR-Pita was flanked by a retrotransposon, which presumably contributed to its multiple translocation across the genome. On the other hand, family member AVR-Pita3, which lacks avirulence activity, was stably located on chromosome 7 in a vast majority of isolates. These results suggest that the diversification in genome location of AVR-Pita in the rice isolates is a consequence of recognition by Pita in rice. We propose a model that the multiple translocation of AVR-Pita may be associated with its frequent loss and recovery mediated by its transfer among individuals in asexual populations. This model implies that the high mobility of AVR-Pita is a key mechanism accounting for the rapid adaptation toward Pita. Dynamic adaptation of some fungal plant pathogens may be achieved by deletion and recovery of avirulence genes using a population as a unit of adaptation

A computational model of lipopolysaccharide-induced nuclear factor kappa B activation:a key signalling pathway in infection-induced preterm labour

Preterm birth is the single biggest cause of significant neonatal morbidity and mortality, and the incidence is rising. Development of new therapies to treat and prevent preterm labour is seriously hampered by incomplete understanding of the molecular mechanisms that initiate labour at term and preterm. Computational modelling provides a new opportunity to improve this understanding. It is a useful tool in (i) identifying gaps in knowledge and informing future research, and (ii) providing the basis for an in silico model of parturition in which novel drugs to prevent or treat preterm labour can be "tested". Despite their merits, computational models are rarely used to study the molecular events initiating labour. Here, we present the first attempt to generate a dynamic kinetic model that has relevance to the molecular mechanisms of preterm labour. Using published data, we model an important candidate signalling pathway in infection-induced preterm labour: that of lipopolysaccharide (LPS) -induced activation of Nuclear Factor kappa B. This is the first model of this pathway to explicitly include molecular interactions upstream of Nuclear Factor kappa B activation. We produced a formalised graphical depiction of the pathway and built a kinetic model based on ordinary differential equations. The kinetic model accurately reproduced published in vitro time course plots of Lipopolysaccharide-induced Nuclear Factor kappa B activation in mouse embryo fibroblasts. In this preliminary work we have provided proof of concept that it is possible to build computational models of signalling pathways that are relevant to the regulation of labour, and suggest that models that are validated with wet-lab experiments have the potential to greatly benefit the field