Neural network‐derived Potts models for structure‐based protein design using backbone atomic coordinates and tertiary motifs

Designing novel proteins to perform desired functions, such as binding or catalysis, is a major goal in synthetic biology. A variety of computational approaches can aid in this task. An energy‐based framework rooted in the sequence‐structure statistics of tertiary motifs (TERMs) can be used for sequence design on predefined backbones. Neural network models that use backbone coordinate‐derived features provide another way to design new proteins. In this work, we combine the two methods to make neural structure‐based models more suitable for protein design. Specifically, we supplement backbone‐coordinate features with TERM‐derived data, as inputs, and we generate energy functions as outputs. We present two architectures that generate Potts models over the sequence space: TERMinator, which uses both TERM‐based and coordinate‐based information, and COORDinator, which uses only coordinate‐based information. Using these two models, we demonstrate that TERMs can be utilized to improve native sequence recovery performance of neural models. Furthermore, we demonstrate that sequences designed by TERMinator are predicted to fold to their target structures by AlphaFold. Finally, we show that both TERMinator and COORDinator learn notions of energetics, and these methods can be fine‐tuned on experimental data to improve predictions. Our results suggest that using TERM‐based and coordinate‐based features together may be beneficial for protein design and that structure‐based neural models that produce Potts energy tables have utility for flexible applications in protein science.     

Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology

Elucidating how an organism''s characteristics emerge from its DNA sequence has been one of the great triumphs of biology. This triumph has cumulated in sophisticated computational models that successfully predict how an organism''s detailed phenotype emerges from its specific genotype. Inspired by that effort''s vision and empowered by its methodologies, a grand challenge is described here that aims to predict the biotic characteristics of an ecosystem, its metaphenome, from nucleic acid sequences of all the species in its community, its metagenome. Meeting this challenge would integrate rapidly advancing abilities of environmental nucleic acids (eDNA and eRNA) to identify organisms, their ecological interactions, and their evolutionary relationships with advances in mechanistic models of complex ecosystems. Addressing the challenge would help integrate ecology and evolutionary biology into a more unified and successfully predictive science that can better help describe and manage ecosystems and the services they provide to humanity.     

基于网络特征的道路生态干扰——以澜沧江流域为例

道路网络对区域景观的生态格局和过程产生较大的影响,作为干扰因子,区域道路网络的特征和所产生的生态干扰水平存在一定的相关性.利用GIS和网络分析法,以澜沧江流域县域为基本单元,分析了研究区各县的道路网络特征指数,在揭示了区域道路网络不同特征之间的规律性的基础上,进一步对区域网络特点和生态干扰之间相关性进行了内在关系的探讨.结果表明,澜沧江流域道路网络结构的空间差异很大,流域内各县的道路网络节点数、连接线数目、α环度、β线点率、γ连接度指数等网络特征因子也存在较大差异;道路密度和道路总长度与区域海拔高度呈现较明显的负相关关系;道路密度和区域道路的廊道密度呈现正相关关系,和区域道路的α指数、β指数和γ指数关系可以用倒数模型来拟合.缓冲区分析表明,耕地比例和道路密度线性相关关系显著,而其他类型相关性较差,但区域综合的人工干扰指数(Hd)(1980,2000)和道路网络的特征指数相关显著,而且不同时期的区域景观的斑块密度、平均斑块面积和区域道路网络特征之间也存在较强的相关性,即网络扩展使得区域生态系统受干扰强度增加,破碎化严重,但较短时期内的生态系统变化和道路网络特征之间相关性不显著.     

Does mixed-species flocking influence how birds respond to a gradient of land-use intensity?

Conservation biology is increasingly concerned with preserving interactions among species such as mutualisms in landscapes facing anthropogenic change. We investigated how one kind of mutualism, mixed-species bird flocks, influences the way in which birds respond to different habitat types of varying land-use intensity. We use data from a well-replicated, large-scale study in Sri Lanka and the Western Ghats of India, in which flocks were observed inside forest reserves, in ‘buffer zones'' of degraded forest or timber plantations, and in areas of intensive agriculture. We find flocks affected the responses of birds in three ways: (i) species with high propensity to flock were more sensitive to land use; (ii) different flock types, dominated by different flock leaders, varied in their sensitivity to land use and because following species have distinct preferences for leaders, this can have a cascading effect on followers'' habitat selection; and (iii) those forest-interior species that remain outside of forests were found more inside flocks than would be expected by chance, as they may use flocks more in suboptimal habitat. We conclude that designing policies to protect flocks and their leading species may be an effective way to conserve multiple bird species in mixed forest and agricultural landscapes.     

丛枝菌根真菌对刺槐幼苗机械损伤响应机制的初步研究

通过对刺槐幼苗每隔3d剪去1片叶片造成持续机械损伤,测定了0~138h抗氧化酶活性变化及刺槐幼苗生长情况;同时使用孔径25μm尼龙网设置三室根箱隔网系统,测定了供体瞬时机械损伤后受体的抗氧化酶活性的持续变化,探讨接种丛枝菌根真菌刺槐幼苗对持续及瞬时机械损伤后的响应机制,以及菌根菌丝桥对刺槐幼苗机械损伤信号的传递特征。结果表明:在持续机械损伤胁迫下,接种丛枝菌根真菌能够促进刺槐幼苗的根系生长、提高幼苗的成活率,接种丛枝菌根真菌的刺槐幼苗成活率及根系鲜重比对照分别增加15.38%和23.52%。瞬时机械损伤后0、48、90、114、138h刺槐幼苗的苯丙氨酸解氨酶(PAL)和过氧化物酶(POD)活性都呈现先增加后降低的趋势,均在90h达到最大值,并且菌根化幼苗的PAL和POD活性显著高于未菌根化幼苗。瞬时机械损伤后,菌根菌丝桥能够介导刺槐幼苗间相关信号的传递,从而引起菌根化受体刺槐幼苗的PAL和POD活性表现出与供体机械损伤幼苗相同的变化趋势。     

The glucose‐deprivation network counteracts lapatinib‐induced toxicity in resistant ErbB2‐positive breast cancer cells

Dynamic interactions between intracellular networks regulate cellular homeostasis and responses to perturbations. Targeted therapy is aimed at perturbing oncogene addiction pathways in cancer, however, development of acquired resistance to these drugs is a significant clinical problem. A network‐based computational analysis of global gene expression data from matched sensitive and acquired drug‐resistant cells to lapatinib, an EGFR/ErbB2 inhibitor, revealed an increased expression of the glucose deprivation response network, including glucagon signaling, glucose uptake, gluconeogenesis and unfolded protein response in the resistant cells. Importantly, the glucose deprivation response markers correlated significantly with high clinical relapse rates in ErbB2‐positive breast cancer patients. Further, forcing drug‐sensitive cells into glucose deprivation rendered them more resistant to lapatinib. Using a chemical genomics bioinformatics mining of the CMAP database, we identified drugs that specifically target the glucose deprivation response networks to overcome the resistant phenotype and reduced survival of resistant cells. This study implicates the chronic activation of cellular compensatory networks in response to targeted therapy and suggests novel combinations targeting signaling and metabolic networks in tumors with acquired resistance.     

Selectivity of stimulus induced responses in cultured hippocampal networks on microelectrode arrays

Sensory information can be encoded using the average firing rate and spike occurrence times in neuronal network responses to external stimuli. Decoding or retrieving stimulus characteristics from the response pattern generally implies that the corresponding neural network has a selective response to various input signals. The role of various spiking activity characteristics (e.g., spike rate and precise spike timing) for basic information processing was widely investigated on the level of neural populations but gave inconsistent evidence for particular mechanisms. Multisite electrophysiology of cultured neural networks grown on microelectrode arrays is a recently developed tool and currently an active research area. In this study, we analyzed the stimulus responses represented by network-wide bursts evoked from various spatial locations (electrodes). We found that the response characteristics, such as the burst initiation time and the spike rate, can be used to retrieve information about the stimulus location. The best selectivity in the response spiking pattern could be found for a small subpopulation of neurones (electrodes) at relatively short post-stimulus intervals. Such intervals were unique for each culture due to the non-uniform organization of the functional connectivity in the network during spontaneous development.     

Scaling up keystone effects from simple to complex ecological networks

Predicting the consequences of species loss requires extending our traditional understanding of simpler dynamic systems of few interacting species to the more complex ecological networks found in natural ecosystems. Especially important is the scaling up of our limited understanding of how and under what conditions loss of ‘keystone’ species causes large declines of many other species. Here we explore how these keystone effects vary among simulations progressively scaled up from simple to more complex systems. Simpler simulations of four to seven interacting species suggest that species up to four links away can strongly alter keystone effects and make the consequences of keystone loss potentially indeterminate in more realistically complex communities. Instead of indeterminacy, we find that more complex networks of up to 32 species generally buffer distant influences such that variation in keystone effects is well predicted by surprisingly local ‘top‐down’, ‘bottom‐up’, and ‘horizontal‘ constraints acting within two links of the keystone subsystem. These results demonstrate that: (1) strong suppression of the competitive dominant by the keystone may only weakly affect subordinate competitors; (2) the community context of the target species determines whether strong keystone effects are realized; (3) simple, measurable, and local attributes of complex communities may explain much of the empirically observed variation in keystone effects; and (4) increasing network complexity per se does not inherently make the prediction of strong keystone effects more complicated.     

综述:阿尔茨海默病的神经影像学研究进展

阿尔茨海默病(Alzheimer's disease,AD)是以记忆和其他高级认知功能下降为特征的神经退行性疾病．早期的神经影像学研究通常是探索AD患者局部脑区的结构和功能变化．随着多模态神经影像技术和人脑连接组学研究方法的发展,研究者已经能够考察AD患者脑结构和功能连接通路．采用这些方法,最近的研究已经发现,AD患者脑网络的连接强度、网络效率、模块化组织和核心脑区连接的下降,并发现这些变化与患者的记忆评分等密切相关．这些新方法和新技术的出现不仅提供了新颖的观点来解释AD病的脑区失连接病理生理机制,而且发现的AD异常脑连接模式可能作为敏感特征应用于AD早期辅助诊断的影像标记物研究．特别重要的是,研究表明,在AD患者脑神经网络出现的异常连接模式,在AD前期即轻度认知障碍期患者中也已出现,表明了将AD影像学研究的重点前移到AD前期这一可治疗阶段的重要性和迫切性．