Kinetic modeling of microbial growth,enzyme activity,and gene deletions: An integrated model of β-glucosidase function in Cellvibrio japonicus

Understanding the complex growth and metabolic dynamics in microorganisms requires advanced kinetic models containing both metabolic reactions and enzymatic regulation to predict phenotypic behaviors under different conditions and perturbations. Most current kinetic models lack gene expression dynamics and are separately calibrated to distinct media, which consequently makes them unable to account for genetic perturbations or multiple substrates. This challenge limits our ability to gain a comprehensive understanding of microbial processes towards advanced metabolic optimizations that are desired for many biotechnology applications. Here, we present an integrated computational and experimental approach for the development and optimization of mechanistic kinetic models for microbial growth and metabolic and enzymatic dynamics. Our approach integrates growth dynamics, gene expression, protein secretion, and gene-deletion phenotypes. We applied this methodology to build a dynamic model of the growth kinetics in batch culture of the bacterium Cellvibrio japonicus grown using either cellobiose or glucose media. The model parameters were inferred from an experimental data set using an evolutionary computation method. The resulting model was able to explain the growth dynamics of C. japonicus using either cellobiose or glucose media and was also able to accurately predict the metabolite concentrations in the wild-type strain as well as in β-glucosidase gene deletion mutant strains. We validated the model by correctly predicting the non-diauxic growth and metabolite consumptions of the wild-type strain in a mixed medium containing both cellobiose and glucose, made further predictions of mutant strains growth phenotypes when using cellobiose and glucose media, and demonstrated the utility of the model for designing industrially-useful strains. Importantly, the model is able to explain the role of the different β-glucosidases and their behavior under genetic perturbations. This integrated approach can be extended to other metabolic pathways to produce mechanistic models for the comprehensive understanding of enzymatic functions in multiple substrates.     

Relationships between population densities and niche‐centroid distances in North American birds

Correlational ecological niche models have seen intensive use and exploration as a means of estimating the limits of actual and potential geographic distributions of species, yet their application to explaining geographic abundance patterns has been debated. We developed a detailed test of this latter possibility based on the North American Breeding Bird Survey. Correlations between abundances and niche‐centroid distances were mostly negative, as per expectations of niche theory and the abundant niche‐centre relationship. The negative relationships were not distributed randomly among species: terrestrial, non‐migratory, small‐bodied, small‐niche‐breadth and restricted‐range species had the strongest negative associations. Distances to niche centroids as estimated from correlational analyses of presence‐only data thus offer a unique means by which to infer geographic abundance patterns, which otherwise are enormously difficult to characterise.     

Evaluating and presenting uncertainty in model‐based unconstrained ordination

Variability in ecological community composition is often analyzed by recording the presence or abundance of taxa in sample units, calculating a symmetric matrix of pairwise distances or dissimilarities among sample units and then mapping the resulting matrix to a low‐dimensional representation through methods collectively called ordination. Unconstrained ordination only uses taxon composition data, without any environmental or experimental covariates, to infer latent compositional gradients associated with the sampling units. Commonly, such distance‐based methods have been used for ordination, but recently there has been a shift toward model‐based approaches. Model‐based unconstrained ordinations are commonly formulated using a Bayesian latent factor model that permits uncertainty assessment for parameters, including the latent factors that correspond to gradients in community composition. While model‐based methods have the additional benefit of addressing uncertainty in the estimated gradients, typically the current practice is to report point estimates without summarizing uncertainty. To demonstrate the uncertainty present in model‐based unconstrained ordination, the well‐known spider and dune data sets were analyzed and shown to have large uncertainty in the ordination projections. Hence to understand the factors that contribute to the uncertainty, simulation studies were conducted to assess the impact of additional sampling units or species to help inform future ordination studies that seek to minimize variability in the latent factors. Accurate reporting of uncertainty is an important part of transparency in the scientific process; thus, a model‐based approach that accounts for uncertainty is valuable. An R package, UncertainOrd , contains visualization tools that accurately represent estimates of the gradients in community composition in the presence of uncertainty.     

杜仲在我国的潜在适生区估计及其生态特征分析

杜仲是我国重要的乡土经济林树种,其产业应用涉及医药、食品、保健、饲料、橡胶、化妆品及园林绿化等领域。预估杜仲在我国的潜在适生区分布,对杜仲资源保护、引种、精细化管护及可持续利用具有重要意义。利用601个杜仲地理分布点和24个环境变量数据,通过MaxEnt模型和空间分析技术预测杜仲潜在适生区分布及其生态特征,结果显示我国杜仲适生区等级可分为4级,其中高适生区38.01万km~2,集中分布在大巴山中低山谷地区、川东平行低山岭谷区、鄂西高原-大类山中低山丘陵谷地区、武陵山中低山谷地区、雪峰山中低山区、川南黔北滇东喀斯特高原中山区以及浙闽中低山丘陵谷地地区。杜仲最适宜生长条件为年平均温度介于11—16℃、年均降水量介于700—1450 mm、温度季节性变化的标准差在820以下、海拔1400 m以下、坡度24°以下。     

The growth and age structure of Chilean jack mackerel (Trachurus murphyi) following its influx to New Zealand waters

The Chilean jack mackerel (Trachurus murphyi) is a predominantly Southeast Pacific Ocean species. It is relatively difficult to determine its age, and multiple studies of its growth off South America have produced markedly different sets of von Bertalanffy parameters. T. murphyi was first identified from New Zealand waters in the mid-1980s and has comprised part of the commercial landings of Trachurus species (along with Trachurus declivis and Trachurus novaezelandiae) since then. Results from 13 years of age determination of New Zealand samples using sectioned otoliths indicate that a partially validated age determination method has been developed, with a precision level (average percentage error) of 4.6%. The best available von Bertalanffy growth parameters for the New Zealand population (sexes combined) are as follows: L_∞, 51.9 cm fork length; K, 0.223 per year; t₀, −0.5 year. Analyses by sex showed that males have a significantly larger L_∞ than females. Estimated annual catch-at-length and catch-at-age distributions from the fishery are presented for 2007–2019. There have been at least two episodes of immigration of T. murphyi from international waters, but little evidence of spawning success to maintain the New Zealand population.     

Using Fecal DNA and Closed-Capture Models to Estimate Feral Horse Population Size

Accurate population estimates provide the foundation for managing feral horses (Equus caballus ferus) across the western United States. Certain feral horse populations are protected by the Wild and Free-Roaming Horses and Burros Act of 1971 and managed by the Bureau of Land Management (BLM) or the United States Forest Service on designated herd management areas (HMAs) or wild horse territories, respectively. Horses are managed to achieve an appropriate management level (AML), which represents the number of horses determined by BLM to contribute to a thriving natural ecological balance and avoid deterioration of the range. To achieve AML for each HMA, BLM resource managers need accurate and precise population estimates. We tested the use of non-invasive fecal samples in a genetic capture-recapture framework to estimate population size in a closed horse population at the Little Book Cliffs HMA, Colorado, USA, with a known size of 153 individuals. We collected 1,957 samples over 3 independent sampling periods in 2014 and amplified them at 8 microsatellite loci. We applied mark-recapture models to determine population size using 954 samples that amplified at all 8 loci. We subsampled and reanalyzed our dataset to simulate different data collection protocols and evaluated effects on accuracy and precision of estimates using N-mixture modeling, full likelihood closed-capture modeling, and capwire single-occasion modeling that used data from all 3 sampling periods. Our model results were accurate and precise for analyses that used data from all 3 occasions; however, capwire single-occasion modeling was not accurate when we analyzed each sampling period separately. For all subsampling analysis scenarios, reducing sample size decreased precision, whether by reducing number of field staff, field days, or geographic areas surveyed on each period. Reducing spatial coverage of the survey area did not result in accurate population estimates and only marginally lowered the number of samples that would need to be collected to maintain accuracy. Because laboratory analysis contributes the greatest expense for this method ($80 U.S./sample), reducing fecal sample size is advantageous. Our results demonstrate that non-invasive sampling combined with good survey design and careful genetic and capture-recapture analyses can provide an alternative method to estimate the number of feral horses in a closed population. This method may be especially appropriate in situations where aerial inventories are not practical or accurate because of low sighting conditions. But the higher costs associated with laboratory sample analyses may reduce the method's feasibility compared to helicopter surveys. © 2021 The Wildlife Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA.     

Transporting stochastic direct and indirect effects to new populations

Transported mediation effects may contribute to understanding how interventions work differently when applied to new populations. However, we are not aware of any estimators for such effects. Thus, we propose two doubly robust, efficient estimators of transported stochastic (also called randomized interventional) direct and indirect effects. We demonstrate their finite sample properties in a simulation study. We then apply the preferred substitution estimator to longitudinal data from the Moving to Opportunity Study, a large‐scale housing voucher experiment, to transport stochastic indirect effect estimates of voucher receipt in childhood on subsequent risk of mental health or substance use disorder mediated through parental employment across sites, thereby gaining understanding of drivers of the site differences.     

Origin and hidden diversity within the poorly known Galápagos snake radiation (Serpentes: Dipsadidae)

Galápagos snakes are among the least studied terrestrial vertebrates of the Archipelago. Here, we provide a phylogenetic analysis and a time calibrated tree for the group, based on a sampling of the major populations known to occur in the Archipelago. Our study revealed the presence of two previously unknown species from Santiago and Rábida Islands, and one from Tortuga, Isabela, and Fernandina. We also recognize six additional species of Pseudalsophis in the Galápagos Archipelago (Pseudalsophis biserialis from San Cristobal, Floreana and adjacent islets; Pseudalsophis hoodensis from Española and adjacent islets; Pseudalsophis dorsalis from Santa Cruz, Baltra, Santa Fé, and adjacent islets; Pseudalsophis occidentalis from Fernandina, Isabela, and Tortuga; Pseudalsophis slevini from Pinzon, and Pseudalsophis steindachneri from Baltra, Santa Cruz and adjacent islets). Our time calibrated tree suggests that the genus Pseudalsophis colonized the Galápagos Archipelago through a single event of oceanic dispersion from the coast of South America that occurred at approximately between 6.9?Ma and 4.4?Ma, near the Miocene/Pliocene boundary.www.zoobank.org/urn:lsid:zoobank.org:pub:2679FD19-01E5-48FE-A0DA-A88FF145DE56     

主观健康测量及定量化估计方法的研究进展

健康风险评估是健康管理的基础工具、前提条件和关键技术.主观健康测量是健康风险评估的重要内容,已逐渐发展成为流行病学、医学统计学、行为医学、全科医学、心理学等多种学科的交叉学科,是健康风险评估研究的热点问题.本文总结了主观健康测量的优缺点,系统回顾了主观健康测量的两类定量化估计方法:计分方法和心理测量学方法,总结了主观健康测量的偏倚及控制方法.随着人类对健康和健康维度的认识已逐步深入,主观健康测量因其诸多优点,并具有较强的理论基础,且定量化估计方法已趋于成熟,目前在国外已被广泛用于健康风险评估和健康测量领域.我国亟需将主观健康测量理念和定量化估计方法引入健康风险评估和健康测量领域.