Microbial Metal Resistance within Structured Environments is Inversely Related to Environmental Pore Size

The physical environments in which microorganisms naturally reside rarely have homogeneous structure, and changes in their porous architecture can have a profound effect on microbial activities – effects that are not typically captured in conventional laboratory studies. Here, to investigate the influence of environmental structure on microbial responses to stress, we constructed structured environments with different pore properties (determined by X-ray Computed Tomography). First, using glass beads in different arrangements and inoculated with the soil yeast Saitozyma podzolica , increases in the average equivalent spherical diameters (ESD) of a structure’s porous architecture led to decreased survival of the yeast under a toxic metal challenge. This relationship was reproduced when yeasts were introduced into additively-manufactured lattice structures, comprising regular arrays with ESDs comparable to those of the bead structures. The pore ESD-dependency of metal resistance was not attributable to differences in cell density in micro-environments delimited by different pore sizes, supporting the inference that pore size specifically is the important parameter here in determining microbial survival of stress. These findings highlight the importance of the physical architecture of an organism’s immediate environment for its response to environmental perturbation, while offering new tools for investigating these interactions in the laboratory. IMPORTANCE Interactions between cells and their structured environments are poorly understood but have significant implications for organismal success in both natural and non-natural settings. This work uses a multidisciplinary approach to develop laboratory models with which the influence of a key parameter of environmental structure – pore size – on cell activities can be dissected. Using these new methods in tandem with additive manufacturing, we demonstrate that resistance of yeast soil-isolates to stress (from a common metal pollutant) is inversely related to pore size of their environment. This has important ramifications for understanding how microorganisms respond to stress in different environments. The findings also establish new pathways for resolving the effects of physical environment on microbial activity, enabling important understanding that is not readily attainable with traditional bulk-sampling and analysis approaches.

Genetic and Environmental Structure of Altruism Characterized by Recipients in Relation to Personality

Background and Objectives: Altruism is a form of prosocial behavior with the goal of increasing the fitness of another individual as a recipient while reducing the fitness of the actor. Although there are many studies on its heterogeneity, only a few behavioral genetic studies have been conducted to examine different recipient types: family members favored by kin selection, the dynamic network of friends and acquaintances as direct reciprocity, and strangers as indirect reciprocity. Materials and Methods: This study investigated the genetic and environmental structure of altruism with reference to recipient types measured by the self-report altruism scale distinguished by the recipient (the SRAS-DR) and examine the relationship to personality dimensions measured by the NEO-FFI with a sample of 461 adult Japanese twin pairs. Results: The present study shows that there is a single common factor of altruism: additive genetic effects explain 51% of altruism without a shared environmental contribution. The genetic contribution of this single common factor is explained by the genetic factors of neuroticism (N), extraversion (E), openness to experience (O), and conscientiousness (C), as well as a common genetic factor specific to altruism. Only altruism toward strangers is affected by shared environmental factors. Conclusions: Different types of altruistic personality are constructed by specific combinational profiles of general personality traits such as the Big Five as well as a genetic factor specific to altruism in each specific way.

Demographic history mediates the effect of stratification on polygenic scores

Population stratification continues to bias the results of genome-wide association studies (GWAS). When these results are used to construct polygenic scores, even subtle biases can cumulatively lead to large errors. To study the effect of residual stratification, we simulated GWAS under realistic models of demographic history. We show that when population structure is recent, it cannot be corrected using principal components of common variants because they are uninformative about recent history. Consequently, polygenic scores are biased in that they recapitulate environmental structure. Principal components calculated from rare variants or identity-by-descent segments can correct this stratification for some types of environmental effects. While family-based studies are immune to stratification, the hybrid approach of ascertaining variants in GWAS but reestimating effect sizes in siblings reduces but does not eliminate stratification. We show that the effect of population stratification depends not only on allele frequencies and environmental structure but also on demographic history.

Infants tailor their attention to maximize learning

Infants’ remarkable learning abilities allow them to rapidly acquire many complex skills. It has been suggested that infants achieve this learning by optimally allocating their attention to relevant stimuli in the environment, but the underlying mechanisms remain poorly understood. Here, we modeled infants’ looking behavior during a learning task through an ideal learner that quantified the informational structure of environmental stimuli. We show that saccadic latencies, looking time, and time spent engaged with a stimulus sequence are explained by the properties of the learning environments, including the level of surprise of the stimulus, overall predictability of the environment, and progress in learning the environmental structure. These findings reveal the factors that shape infants’ advanced learning, emphasizing their predisposition to seek out stimuli that maximize learning.

The influence of internal models on feedback-related brain activity

Decision making relies on the interplay between two distinct learning mechanisms, namely habitual model-free learning and goal-directed model-based learning. Recent literature suggests that this interplay is significantly shaped by the environmental structure as represented by an internal model. We employed a modified two-stage but one-decision Markov decision task to investigate how two internal models differing in the predictability of stage transitions influence the neural correlates of feedback processing. Our results demonstrate that fronto-central theta and the feedback-related negativity (FRN), two correlates of reward prediction errors in the medial frontal cortex, are independent of the internal representations of the environmental structure. In contrast, centro-parietal delta and the P3, two correlates possibly reflecting feedback evaluation in working memory, were highly susceptible to the underlying internal model. Model-based analyses of single-trial activity showed a comparable pattern, indicating that while the computation of unsigned reward prediction errors is represented by theta and the FRN irrespective of the internal models, the P3 adapts to the internal representation of an environment. Our findings further substantiate the assumption that the feedback-locked components under investigation reflect distinct mechanisms of feedback processing and that different internal models selectively influence these mechanisms.