Ecological and evolutionary consequences of selective interspecific information use

Recent work has shown that animals frequently use social information from individuals of their own species as well as from other species; however, the ecological and evolutionary consequences of this social information use remain poorly understood. Additionally, information users may be selective in their social information use, deciding from whom and how to use information, but this has been overlooked in an interspecific context. In particular, the intentional decision to reject a behaviour observed via social information has received less attention, although recent work has indicated its presence in various taxa. Based on existing literature, we explore in which circumstances selective interspecific information use may lead to different ecological and coevolutionary outcomes between two species, such as explaining observed co-occurrences of putative competitors. The initial ecological differences and the balance between the costs of competition and the benefits of social information use potentially determine whether selection may lead to trait divergence, convergence or coevolutionary arms race between two species. We propose that selective social information use, including adoption and rejection of behaviours, may have far-reaching fitness consequences, potentially leading to community-level eco-evolutionary outcomes. We argue that these consequences of selective interspecific information use may be much more widespread than has thus far been considered.     

Mechanisms of group-hunting in vertebrates

Group-hunting is ubiquitous across animal taxa and has received considerable attention in the context of its functions. By contrast much less is known about the mechanisms by which grouping predators hunt their prey. This is primarily due to a lack of experimental manipulation alongside logistical difficulties quantifying the behaviour of multiple predators at high spatiotemporal resolution as they search, select, and capture wild prey. However, the use of new remote-sensing technologies and a broadening of the focal taxa beyond apex predators provides researchers with a great opportunity to discern accurately how multiple predators hunt together and not just whether doing so provides hunters with a per capita benefit. We incorporate many ideas from collective behaviour and locomotion throughout this review to make testable predictions for future researchers and pay particular attention to the role that computer simulation can play in a feedback loop with empirical data collection. Our review of the literature showed that the breadth of predator:prey size ratios among the taxa that can be considered to hunt as a group is very large (<10⁰ to >10²). We therefore synthesised the literature with respect to these predator:prey ratios and found that they promoted different hunting mechanisms. Additionally, these different hunting mechanisms are also related to particular stages of the hunt (search, selection, capture) and thus we structure our review in accordance with these two factors (stage of the hunt and predator:prey size ratio). We identify several novel group-hunting mechanisms which are largely untested, particularly under field conditions, and we also highlight a range of potential study organisms that are amenable to experimental testing of these mechanisms in connection with tracking technology. We believe that a combination of new hypotheses, study systems and methodological approaches should help push the field of group-hunting in new directions.     

The population-dynamic functions of seed dispersal

We summarize some of the population-dynamic consequences of the mosaic structure of plant populations for the evolution of seed dispersal. A fairly elaborated set of theoretical ideas exist regarding the evolution of dispersal and we have synthesized some of them in an attempt to make them more accessible to field ecologists. We consider the relationship of these general theoretical ideas to our understanding of fruit and seed dispersal.We develop three related models to describe the similarities and differences in how dispersal functions for risk reduction (bet hedging), escaping the negative consequences of crowding, and escaping high concentrations of relatives. We also briefly discuss directed dispersal as a fourth population-dynamic aspect of dispersal. Dispersal can have a risk-reducing function only when there is global (metapopulation) temporal variance in success. Dispersal to escape the negative consequences of crowding requires only spatial and local temporal environmental variation. Dispersal for escaping high concentrations of relatives requires no environmental variation, but does require genetic population structure. Directed dispersal, defined as non-random into particular patch types contingent on the expectation of local success, is always valuable when possible and represents an advantage independent the others which can occur with random dispersal.In an effort to accommodate for the differences between simple mathematical models and the behavior of complex natural fruit and seed dispersal systems we have discussed the following issues: actual patterns of patch structure and dispersal distance; the implications of plant cosexuality, perenniality, and allocation costs of dispersal structures; and the impact of the detailed nature of density dependence, breeding systems, and genetic structure. We briefly compare the population-dynamic functions of dispersal presented here with the widely cited functions of colonization, escape, and directed dispersal. Finally, we suggest how the theoretical models can be used with field data to estimate the fitness consequences of dispersal.     

Semiparametric estimation of the transformation model by leveraging external aggregate data in the presence of population heterogeneity

Leveraging information in aggregate data from external sources to improve estimation efficiency and prediction accuracy with smaller scale studies has drawn a great deal of attention in recent years. Yet, conventional methods often either ignore uncertainty in the external information or fail to account for the heterogeneity between internal and external studies. This article proposes an empirical likelihood-based framework to improve the estimation of the semiparametric transformation models by incorporating information about the t-year subgroup survival probability from external sources. The proposed estimation procedure incorporates an additional likelihood component to account for uncertainty in the external information and employs a density ratio model to characterize population heterogeneity. We establish the consistency and asymptotic normality of the proposed estimator and show that it is more efficient than the conventional pseudopartial likelihood estimator without combining information. Simulation studies show that the proposed estimator yields little bias and outperforms the conventional approach even in the presence of information uncertainty and heterogeneity. The proposed methodologies are illustrated with an analysis of a pancreatic cancer study.     

Dynamic genome-scale modeling of Saccharomyces cerevisiae unravels mechanisms for ester formation during alcoholic fermentation

Fermentation employing Saccharomyces cerevisiae has produced alcoholic beverages and bread for millennia. More recently, S. cerevisiae has been used to manufacture specific metabolites for the food, pharmaceutical, and cosmetic industries. Among the most important of these metabolites are compounds associated with desirable aromas and flavors, including higher alcohols and esters. Although the physiology of yeast has been well-studied, its metabolic modulation leading to aroma production in relevant industrial scenarios such as winemaking is still unclear. Here we ask what are the underlying metabolic mechanisms that explain the conserved and varying behavior of different yeasts regarding aroma formation under enological conditions? We employed dynamic flux balance analysis (dFBA) to answer this key question using the latest genome-scale metabolic model (GEM) of S. cerevisiae. The model revealed several conserved mechanisms among wine yeasts, for example, acetate ester formation is dependent on intracellular metabolic acetyl-CoA/CoA levels, and the formation of ethyl esters facilitates the removal of toxic fatty acids from cells using CoA. Species-specific mechanisms were also found, such as a preference for the shikimate pathway leading to more 2-phenylethanol production in the Opale strain as well as strain behavior varying notably during the carbohydrate accumulation phase and carbohydrate accumulation inducing redox restrictions during a later cell growth phase for strain Uvaferm. In conclusion, our new metabolic model of yeast under enological conditions revealed key metabolic mechanisms in wine yeasts, which will aid future research strategies to optimize their behavior in industrial settings.     

Elastic priors to dynamically borrow information from historical data in clinical trials

Use of historical data and real-world evidence holds great potential to improve the efficiency of clinical trials. One major challenge is to effectively borrow information from historical data while maintaining a reasonable type I error and minimal bias. We propose the elastic prior approach to address this challenge. Unlike existing approaches, this approach proactively controls the behavior of information borrowing and type I errors by incorporating a well-known concept of clinically significant difference through an elastic function, defined as a monotonic function of a congruence measure between historical data and trial data. The elastic function is constructed to satisfy a set of prespecified criteria such that the resulting prior will strongly borrow information when historical and trial data are congruent, but refrain from information borrowing when historical and trial data are incongruent. The elastic prior approach has a desirable property of being information borrowing consistent, that is, asymptotically controls type I error at the nominal value, no matter that historical data are congruent or not to the trial data. Our simulation study that evaluates the finite sample characteristic confirms that, compared to existing methods, the elastic prior has better type I error control and yields competitive or higher power. The proposed approach is applicable to binary, continuous, and survival endpoints.     

Anti-CRISPR Discovery: Using Magnets to Find Needles in Haystacks

CRISPR-Cas immune systems in bacteria and archaea protect against viral infection, which has spurred viruses to develop dedicated inhibitors of these systems called anti-CRISPRs (Acrs). Like most host-virus arms races, many diverse examples of these immune and counter-immune proteins are encoded by the genomes of bacteria, archaea, and their viruses. For the case of Acrs, it is almost certain that just a small minority of nature’s true diversity has been described. In this review, I discuss the various approaches used to identify these Acrs and speculate on the future for Acr discovery. Because Acrs can determine infection outcomes in nature and regulate CRISPR-Cas activities in applied settings, they have a dual importance to both host-virus conflicts and emerging biotechnologies. Thus, revealing the largely hidden world of Acrs should provide important lessons in microbiology that have the potential to ripple far beyond the field.     

Investigation of <i>GhFAT</i> Genes Related to Seed Oil Content and Fatty Acid Composition in <i>Gossypium hirsutum</i> L.

Fatty Acyl-ACP thioesterase (FAT) is a key enzyme controlling oil biosynthesis in plant seeds. FATs can be divided into two subfamilies, FATA and FATB according to their amino acid sequences and substrate specificity. The Upland cotton genome contains 20 GhFAT genes, amongst which 6 genes were of the GhFATA subfamily and 14 of the GhFATB subfamily. The 20 GhFAT genes are unevenly distributed on 14 chromosomes. The GhFATA genes have 5 or 7 exons and the GhFATB genes have 6 or 7 exons. All GhFAT proteins have the conserved Acyl-ACP_TE domain and PLN02370 super family, the typical characteristics of plant thioesterases. Analyses of the expression level of GhFATs and the compositions of fatty acid in 5–60 days-post-anthesis seeds showed that the ratio of saturated fatty acids to unsaturated fatty acids was consistent with the expression profile of GhFATB12, GhFATB3, and GhFATB10; the ratio of monounsaturated fatty acid to polyunsaturated fatty acids was consistent with the expression profile of GhFATA3. The oil contents of mature cottonseeds were positively correlated with the contents of palmitic acid and linolenic acid as well as seed vigor. These results provide essential information for further exploring the role(s) of the specific GhFATs in determining oil biosynthesis and cottonseed compositions.     

CHIRBASE,a graphical molecular database on the separation of enantiomers by liquid-, supercritical fluid-, and gas chromatography

In order to cope with the increasing number of publications on the separation of enantiomers by chromatography on a chiral stationary phase, the graphical molecular database CHIRBASE was created. In the present state, the database package covers information (structural, bibiographic, and chromatographic data) on liquid-, supercritical fluid-, and gas chromatography; other methods will follow. CHIRBASE, running on the MDL software Chembase®, meets the requirements of contemporary information management in the chemical and pharmaceutical industry. (Detailed information including a demo-version of each part of CHIRBASE can be obtained from the authors on request.) © 1993 Wiley-Liss, Inc.     

攀西高原不同轮作制度下土壤固氮微生物nifH基因多样性与群落结构特征

[背景]关于高原生境轮作制度对土壤固氮微生物群落组成及多样性的影响研究尚少。[目的]深入认识攀西高原不同轮作制度对农田土壤肥力及土壤固氮微生物nifH基因群落结构与多样性的影响,以期建立合理的轮作制度。[方法]以凉山州冕宁县不同作物轮作制度[包括光叶紫花苕-烤烟(分轮作15年和20年两种,分别为G1和G2)、苦荞-烤烟(KQ)、大麦-烤烟(DM)和撂荒(CK)]的土壤为研究对象,通过化学分析和Illumina MiSeq技术,对土壤理化性质、土壤固氮微生物nifH基因多样性及群落组成进行分析。[结果]撂荒土壤全氮、铵态氮、硝态氮、有机碳和含水量最显著(P<0.05)。KQ轮作下土壤有效磷和速效钾分别提高了43.0%和2.60%,而DM轮作下的土壤理化性质均下降。土壤固氮酶活以撂荒土壤最高,G2轮作最低。土壤固氮微生物nifH基因多样性以G1轮作最高、G2轮作最低,门水平上以变形菌门(Proteobacteria)是优势共有nifH基因类群,相对丰度占群落的63.0%-92.4%;属水平上,偶氮氢单胞菌属(Azohydromonas)是不同轮作制度下的优势物种,慢生根瘤属(Brad...