The evolution of helping and harming on graphs: the return of the inclusive fitness effect

Evolutionary graph theory has been proposed as providing new fundamental rules for the evolution of co‐operation and altruism. But how do these results relate to those of inclusive fitness theory? Here, we carry out a retrospective analysis of the models for the evolution of helping on graphs of Ohtsuki et al. [Nature (2006) 441, 502] and Ohtsuki & Nowak [Proc. R. Soc. Lond. Ser. B Biol. Sci (2006) 273, 2249]. We show that it is possible to translate evolutionary graph theory models into classical kin selection models without disturbing at all the mathematics describing the net effect of selection on helping. Model analysis further demonstrates that costly helping evolves on graphs through limited dispersal and overlapping generations. These two factors are well known to promote relatedness between interacting individuals in spatially structured populations. By allowing more than one individual to live at each node of the graph and by allowing interactions to vary with the distance between nodes, our inclusive fitness model allows us to consider a wider range of biological scenarios leading to the evolution of both helping and harming behaviours on graphs.     

Synergy and group size in microbial cooperation

Abstract Microbes produce many molecules that are important for their growth and development, and the exploitation of these secretions by nonproducers has recently become an important paradigm in microbial social evolution. Although the production of these public-goods molecules has been studied intensely, little is known of how the benefits accrued and the costs incurred depend on the quantity of public-goods molecules produced. We focus here on the relationship between the shape of the benefit curve and cellular density, using a model assuming three types of benefit functions: diminishing, accelerating, and sigmoidal (accelerating and then diminishing). We classify the latter two as being synergistic and argue that sigmoidal curves are common in microbial systems. Synergistic benefit curves interact with group sizes to give very different expected evolutionary dynamics. In particular, we show that whether and to what extent microbes evolve to produce public goods depends strongly on group size. We show that synergy can create an "evolutionary trap" that can stymie the establishment and maintenance of cooperation. By allowing density-dependent regulation of production (quorum sensing), we show how this trap may be avoided. We discuss the implications of our results on experimental design.     

Nucleo-cytoplasmic transport of U snRNPs: definition of a nuclear location signal in the Sm core domain that binds a transport receptor independently of the m3G cap.

We have investigated the nuclear transport of U1 and U5 snRNPs by microinjection studies in oocytes from Xenopus laevis using snRNP particles prepared by reconstitution in vitro. Competition studies with snRNPs showed that the Sm core domain of U1 snRNPs contains a nuclear location signal that acts independently of the m3G cap. The transport of U1 snRNP can be blocked by saturation with competitor U1 snRNPs or by U5 snRNPs, which indicates that the signals on the respective Sm core domains interact with the same transport receptors. Further, by using a minimal U1 snRNP particle reconstituted in vitro and containing only the Sm core RNP domain and lacking stem-loops I to III of U1 RNA, we show that this is targeted actively to the nucleus, in spite of the absence of the m3G cap. This indicates that under certain conditions the NLS in the Sm core domain not only is an essential, but may also be a sufficient condition for nuclear targeting. We propose that the RNA structure of a given snRNP particle determines at least in part whether the particle's m3G cap is required for nuclear transport or can be dispensed with.     

Viral evolution and interferon resistance of hepatitis C virus RNA replication in a cell culture model

Hepatitis C virus (HCV) replicates through an error-prone process that may support the evolution of genetic variants resistant to the host cell antiviral response and interferon (IFN)-based therapy. We evaluated HCV-IFN interactions within a long-term culture system of Huh7 cell lines harboring different variants of an HCV type 1b subgenomic RNA replicon that differed at only two sites within the NS5A-encoding region. A replicon with a K insertion at HCV codon 2040 replicated efficiently and exhibited sequence stability in the absence of host antiviral pressure. In contrast, a replicon with an L2198S point mutation replicated poorly and triggered a cellular response characterized by IFN-beta production and low-level IFN-stimulated gene (ISG) expression. When maintained in long term-culture, the L2198S RNA evolved into a stable high-passage (HP) variant with six additional point mutations throughout the HCV protein-encoding region that enhanced viral replication. The HP RNA transduced Huh7 cells with more than 1,000-fold greater efficiency than its L2198S progenitor or the K2040 sequence. Replication of the HP RNA resisted suppression by IFN-alpha treatment and was associated with virus-directed reduction in host cell expression of ISG56, an antagonist of HCV RNA translation. Accordingly, the HP RNA was retained within polyribosome complexes in vivo that were refractory to IFN-induced disassembly. These results identify ISG56 as a translational control effector of the host response to HCV and provide direct evidence to link this response to viral sequence evolution, ISG regulation, and selection of the IFN-resistant viral phenotype.     

The effects of changes in consequences on hens' performance in delayed-matching-to-sample tasks

A delayed-matching-to-sample (DMTS) task was used to investigate remembering with domestic hens. In Conditions 1 and 3 of Experiment 1, six hens responded under a mixed-delay procedure with delays of 0.25, 2, and 8 s. In Condition 2, the reinforcer for correct responding was delayed for 6 s after each correct matching response on 2-s delay trials. In Condition 1, discrimination performance decreased monotonically over the three delays. With the delay to the reinforcer, the decreases were non-monotonic as a result of the considerable drop in the accuracy of discrimination on the 2-s delay trials. Performance at the 2-s delay did not recover completely in Condition 3. In Conditions 1 and 3 of Experiment 2, five hens responded under a mixed-delay procedure with delays of 0, 4, and 16 s. In Condition 2 no reinforcers were provided for correct responding on 0- and 16-s delay trials. When reinforcers were available on all trials discrimination performance decreased monotonically with delay. There were non-monotonic changes in discrimination with delay when there was extinction at two delays resulting mainly from a large drop in discrimination performance at 0 s. In addition, response latencies increased markedly at the two delays associated with extinction. Performance recovered completely in Condition 3. The data support the ideas that remembering involves a temporal discrimination that the effects of delaying reinforcement and removing reinforcement may differ, and that the measurement of response latencies may be a useful tool in DMTS procedures.     

Regulating intracellular antiviral defense and permissiveness to hepatitis C virus RNA replication through a cellular RNA helicase, RIG-I

Virus-responsive signaling pathways that induce alpha/beta interferon production and engage intracellular immune defenses influence the outcome of many viral infections. The processes that trigger these defenses and their effect upon host permissiveness for specific viral pathogens are not well understood. We show that structured hepatitis C virus (HCV) genomic RNA activates interferon regulatory factor 3 (IRF3), thereby inducing interferon in cultured cells. This response is absent in cells selected for permissiveness for HCV RNA replication. Studies including genetic complementation revealed that permissiveness is due to mutational inactivation of RIG-I, an interferon-inducible cellular DExD/H box RNA helicase. Its helicase domain binds HCV RNA and transduces the activation signal for IRF3 by its caspase recruiting domain homolog. RIG-I is thus a pathogen receptor that regulates cellular permissiveness to HCV replication and, as an interferon-responsive gene, may play a key role in interferon-based therapies for the treatment of HCV infection.     

The peptidyltransferase centre of the Escherichia coli ribosome. The histidine of protein L16 affects the reconstitution and control of the active centre but is not essential for release-factor-mediated peptidyl-tRNA hydrolysis and peptide bond formation

Modification of the Escherichia coli 50S ribosomal subunit with histidine-specific diethyl pyrocarbonate affects peptide bond formation and release-factor-dependent peptidyl-tRNA hydrolysis. Unmodified L16 can restore activity to a split protein fraction from the altered subunit but other proteins of the core also contain histidine residues important for the activity of the peptidyltransferase centre. When isolated and purified by centrifugation, particles reconstituted with unmodified proteins and modified L16 do not retain the altered L16. The modified protein does mediate the partial restoration of peptide bond formation and release-factor-2 activities to these particles. It must be exerting its effect during the assembly of the peptidyltransferase centre in the reconstituted particle. A particle could be reconstituted which lacks L16 and has significant activity in peptide bond formation and peptidyl-tRNA hydrolysis. L16 stimulates these activities. A tighter ribosomal binding of the release factor 2, dependent upon the absence of protein L11, can in part compensate for the loss of activity of the peptidyltransferase centre when it is assembled with either modified L16 or in the absence of L16. The protein and its histidine residue seem important, therefore, for the peptidyltransferase centre to be formed in the correct conformation but not essential for activity once the centre is assembled.     

The ribosomal binding domain of the Escherichia coli release factors. Modification of tyrosine in the N-terminal domain of ribosomal protein L11 affects release factors 1 and 2 differentially

Ribosomal protein L11 is one of only two ribosomal proteins significantly iodinated when Escherichia coli 50 S subunits are modified by immobilized lactoperoxidase, and the major target has been shown previously to be tyrosine at position 7 in the N-terminal domain. This modification reduces in vitro termination activity with release factor (RF)-1 by 70-90%, but RF-2 activity is less affected (30-50%). The loss of activity parallels incorporation of iodine into the subunit. The 50 S subunits from L11-lacking strains of bacteria have highly elevated activity with RF-2 and low activity with RF-1. The iodination does not affect RF-2 activity but reduces the RF-1 activity further. Ribosomal proteins, L2, L6, and L25, are significantly labeled in L11-lacking ribosomes in contrast to the control 50 S subunits. L11 has been modified in isolation and incorporated back efficiently into L11-lacking ribosomes. This L11, iodinated also predominantly at Tyr 7, is unable to restore RF-1 activity to L11-lacking ribosomes in contrast to mock-iodinated protein. These results suggest the involvement of the N terminus of L11 in the binding domain of the bacterial release factors and indicate that there are subtle differences in how the two factors interact with the ribosome.     

Bayesian Dynamical Systems Modelling in the Social Sciences

Data arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear functions that capture interactions between variables, employing Bayes factor to decide how many interaction terms should be included in the model. This method punishes overly complicated models and identifies models with the most explanatory power. We illustrate our approach on the classic example of relating democracy and economic growth, identifying non-linear relationships between these two variables. We show how multiple variables and variable lags can be accounted for and provide a toolbox in R to implement our approach.