编译 | 未玖
Science, 7 OCTOBER 2022, VOL 378, ISSUE 6615
《科学》2022年10月7日，第378卷，6615期
材料科学Materials Science
Machine learning–enabled high-entropy alloy discovery
机器学习助力高熵合金发现
▲ 作者：ZIYUAN RAO, PO-YEN TUNG, RUIWEN XIE, YE WEI, HONGBIN ZHANG, ALBERTO FERRARI, ET AL.
▲ 链接：
https://www.science.org/doi/10.1126/science.abo4940
▲ 摘要：
高熵合金是多种主元素的固溶体，能够达到稀释材料无法达到的成分和性能状态。然而，发现这些珍贵性质往往出于偶然，因为热力学合金设计规则在高维组成空间并不适用。
研究组提出了一种主动学习策略，基于非常稀少的数据，在几乎无限的成分空间中加速高熵因瓦合金的设计。该方法以闭环方式工作，将机器学习与密度泛函理论、热力学计算和实验相结合。
在处理和表征了数百万种可能成分中的17种新合金后，研究组确定了两种热膨胀系数极低（300 K时约为2×10?6/K）的高熵因瓦合金。该策略有助于快速和自动化发现具有最佳热、磁和电性能高熵合金。
▲ Abstract：
High-entropy alloys are solid solutions of multiple principal elements that are capable of reaching composition and property regimes inaccessible for dilute materials. Discovering those with valuable properties, however, too often relies on serendipity, because thermodynamic alloy design rules alone often fail in high-dimensional composition spaces. We propose an active learning strategy to accelerate the design of high-entropy Invar alloys in a practically infinite compositional space based on very sparse data. Our approach works as a closed-loop, integrating machine learning with density-functional theory, thermodynamic calculations, and experiments. After processing and characterizing 17 new alloys out of millions of possible compositions, we identified two high-entropy Invar alloys with extremely low thermal expansion coefficients around 2 × 10?6 per degree kelvin at 300 kelvin. We believe this to be a suitable pathway for the fast and automated discovery of high-entropy alloys with optimal thermal, magnetic, and electrical properties.
Hallucinating symmetric protein assemblies
“幻觉法”生成对称蛋白质组合
▲ 作者：B. I. M. WICKY, L. F. MILLES, A. COURBET, R. J. RAGOTTE, J. DAUPARAS, E. KINFU, ET AL.
▲ 链接：
https://www.science.org/doi/10.1126/science.add1964
▲ 摘要：
深度学习生成方法提供了一个机会，可广泛探索超越天然蛋白质序列和结构的蛋白质结构空间。
研究组使用深度网络“幻觉法”生成了广泛的对称蛋白质同源寡聚体，只需给定原聚体的数量和长度。七种设计的晶体结构与计算模型非常相似（中位均方根偏差：0.6埃），具有高达1550个残基和C33对称性的巨型10纳米环的三种冷冻电子显微镜结构；所有这些都与先前解析的结构有很大不同。
该研究结果突出了利用深度学习可生成新蛋白质结构的丰富多样性，并为纳米机器和生物材料越来越复杂的组件设计铺平了道路。
▲ Abstract：
Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here, we use deep network hallucination to generate a wide range of symmetric protein homo-oligomers given only a specification of the number of protomers and the protomer length. Crystal structures of seven designs are very similar to the computational models (median root mean square deviation: 0.6 angstroms), as are three cryo–electron microscopy structures of giant 10-nanometer rings with up to 1550 residues and C33 symmetry; all differ considerably from previously solved structures. Our results highlight the rich diversity of new protein structures that can be generated using deep learning and pave the way for the design of increasingly complex components for nanomachines and biomaterials.
生态学Ecology
Emergent phases of ecological diversity and dynamics mapped in microcosms
微观世界中生态多样性和动态的涌现阶段
▲ 作者：JILIANG HU, DANIEL R. AMOR, MATTHIEU BARBIER, GUY BUNIN AND JEFF GORE.
▲ 链接：
https://www.science.org/doi/10.1126/science.abm7841
▲ 摘要：
从热带森林到肠道微生物群，生态群落承载着大量共存物种。除了高度的生物多样性，群落还表现出一系列复杂的动态，很难在统一框架下加以解释。
利用细菌微观世界，研究组对理论进行了直接测试，预测简单的群落-水平特征决定群落的紧急行为。随着物种数量或相互作用强度的增加，研究组表明微生物生态系统在三个不同的动态阶段之间转变，从所有物种共存的稳定平衡到部分共存，再到物种丰度出现持续波动，其顺序与理论预测的顺序一致。
在固定条件下，高生物多样性和波动相辅相成。该研究结果表明了生态群落多样性和动态的可预测的涌现模式。
▲ Abstract：
From tropical forests to gut microbiomes, ecological communities host notably high numbers of coexisting species. Beyond high biodiversity, communities exhibit a range of complex dynamics that are difficult to explain under a unified framework. Using bacterial microcosms, we performed a direct test of theory predicting that simple community-level features dictate emergent behaviors of communities. As either the number of species or the strength of interactions increases, we show that microbial ecosystems transition between three distinct dynamical phases, from a stable equilibrium in which all species coexist to partial coexistence to emergence of persistent fluctuations in species abundances, in the order predicted by theory. Under fixed conditions, high biodiversity and fluctuations reinforce each other. Our results demonstrate predictable emergent patterns of diversity and dynamics in ecological communities.
Electrochemical potential enables dormant spores to integrate environmental signals
电化学电位使休眠孢子能够整合环境信号
▲ 作者：KAITO KIKUCHI, LETICIA GALERA-LAPORTA, COLLEEN WEATHERWAX, JAMIE Y. LAM, EUN CHAE MOON, EMMANUEL A. THEODORAKIS, ET AL.
▲ 链接：
https://www.science.org/doi/10.1126/science.abl7484
▲ 摘要：
细菌孢子的休眠状态通常被认为缺乏生物活性。
研究组表明，尽管孢子持续休眠，但随着时间的推移，孢子可以通过预先存在的电化学电位整合环境信号。具体而言，他们研究了数千个单独的枯草芽孢杆菌孢子，其在暴露于短暂营养脉冲时仍保持休眠状态。
在细菌电生理学数学模型的指导下，研究组通过基因和化学靶向钾离子通量来调整退出休眠的决定。他们证实了短营养脉冲导致持久性孢子的电化学电位出现阶梯式变化。
在休眠期间，随着时间的推移，孢子逐渐释放其储存的电化学电位以整合细胞外信息。该发现揭示了在生理非活性细胞中运行的决策机制。
▲ Abstract：
The dormant state of bacterial spores is generally thought to be devoid of biological activity. We show that despite continued dormancy, spores can integrate environmental signals over time through a preexisting electrochemical potential. Specifically, we studied thousands of individual Bacillus subtilis spores that remain dormant when exposed to transient nutrient pulses. Guided by a mathematical model of bacterial electrophysiology, we modulated the decision to exit dormancy by genetically and chemically targeting potassium ion flux. We confirmed that short nutrient pulses result in step-like changes in the electrochemical potential of persistent spores. During dormancy, spores thus gradually release their stored electrochemical potential to integrate extracellular information over time. These findings reveal a decision-making mechanism that operates in physiologically inactive cells.
公共卫生Public Health
The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance
非洲不断演变的SARS-CoV-2疫情：迅速扩大的基因组监测的见解
▲ 作者：HOURIIYAH TEGALLY, JAMES E. SAN, MATTHEW COTTON, MONIKA MOIR, BRYAN TEGOMOH, GERALD MBOOWA, ET AL.
▲ 链接：
https://www.science.org/doi/10.1126/science.abq5358
▲ 摘要：
过去一年对非洲SARS-CoV-2测序的投资，导致生成和用于跟踪该大陆大流行的序列数量大幅增加，目前已超过10万个基因组。
研究结果显示，能够在本国内进行测序的非洲国家数量有所增加，并强调本地测序能够加快周转时间和更定期的常规监测。尽管检测比例较低，但这项基因组监测研究的结果强调了大流行的异质性，并阐明了备受关注的变异株（尤其是α、β、δ和奥密克戎）在非洲大陆的独特扩散动态。
由于该病毒继续进化，同时非洲大陆面临着许多新出现和再出现的传染病威胁，因此需要对非洲的诊断和基因组监测进行持续投资。这些投资对于大流行病的防范和应对至关重要，并将为21世纪的非洲大陆健康服务。
▲ Abstract：
Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern—particularly Alpha, Beta, Delta, and Omicron—on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century.
Heavy-tailed sexual contact networks and monkeypox epidemiology in the global outbreak, 2022
2022年全球疫情中重尾性接触网络和猴痘流行病学
▲ 作者：AKIRA ENDO, HIROAKI MURAYAMA, SAM ABBOTT, RUWAN RATNAYAKE, CARL A. B. PEARSON, W. JOHN EDMUNDS, ET AL.
▲ 链接：
https://www.science.org/doi/10.1126/science.add4507
▲ 摘要：
2022年5月确认的猴痘在非流行地区暴发显示出与以往输入性暴发不同的流行病学特征，最显著的是在男男性行为者（MSM）中观察到其增长和优势。
研究组使用了一个与经验性伴侣关系数据相契合的传播模型，以表明重尾性伴侣关系分布（少数个体拥有过多性伴侣）可以解释猴痘在MSM中的持续增长，尽管以前没有这种模式。猴痘在MSM性传播网络上的基本繁殖数（R0）可能大大高于1，这对疫情控制带来了挑战。
研究组呼吁有必要确保提供支持和针对性信息，以促进有大量性伴侣MSM的猴痘预防和早期发现。
▲ Abstract：
The outbreak of monkeypox across non-endemic regions confirmed in May 2022 shows epidemiological features distinct from previously imported outbreaks, most notably its observed growth and predominance amongst men who have sex with men (MSM). We use a transmission model fitted to empirical sexual partnership data to show that the heavy-tailed sexual partnership distribution, in which a handful of individuals have disproportionately many partners, can explain the sustained growth of monkeypox among MSM despite the absence of such patterns previously. We suggest that the basic reproduction number (R0) for monkeypox over the MSM sexual network may be substantially above 1, which poses challenges to outbreak containment. Ensuring support and tailored messaging to facilitate prevention and early detection among MSM with high numbers of partners is warranted.