Evolutionary relationships and sequence-structure determinants in human SARS coronavirus-2 spike proteins for host receptor recognition

Coronavirus disease 2019 (COVID-19) is a pandemic infectious disease caused by novel severe acute respiratory syndrome coronavirus-2 (SARS CoV-2). The SARS CoV-2 is transmitted more rapidly and readily than SARS CoV. Both, SARS CoV and SARS CoV-2 via their glycosylated spike proteins recognize the human angiotensin converting enzyme-2 (ACE-2) receptor. We generated multiple sequence alignments and phylogenetic trees for representative spike proteins of SARS CoV and SARS CoV-2 from various host sources in order to analyze the specificity in SARS CoV-2 spike proteins required for causing infection in humans. Our results show that among the genomes analyzed, two sequence regions in the N-terminal domain “MESEFR” and “SYLTPG” are specific to human SARS CoV-2. In the receptor-binding domain, two sequence regions “VGGNY“ and ”EIYQAGSTPCNGV” and a disulfide bridge connecting 480C and 488C in the extended loop are structural determinants for the recognition of human ACE-2 receptor. The complete genome analysis of representative SARS CoVs from bat, civet, human host sources, and human SARS CoV-2 identified the bat genome (GenBank code: MN996532.1) as closest to the recent novel human SARS CoV-2 genomes. The bat SARS CoV genomes (GenBank codes: MG772933 and MG772934) are evolutionary intermediates in the mutagenesis progression toward becoming human SARS CoV-2.     

Accuracy of predicting genomic breeding values for carcass merit traits in Angus and Charolais beef cattle

Accuracy of predicting genomic breeding values for carcass merit traits including hot carcass weight, longissimus muscle area (REA), carcass average backfat thickness (AFAT), lean meat yield (LMY) and carcass marbling score (CMAR) was evaluated based on 543 Angus and 400 Charolais steers genotyped on the Illumina BovineSNP50 Beadchip. For the genomic prediction within Angus, the average accuracy was 0.35 with a range from 0.32 (LMY) to 0.37 (CMAR) across different training/validation data‐splitting strategies and statistical methods. The within‐breed genomic prediction for Charolais yielded an average accuracy of 0.36 with a range from 0.24 (REA) to 0.46 (AFAT). The across‐breed prediction had the lowest accuracy, which was on average near zero. When the data from the two breeds were combined to predict the breeding values of either breed, the prediction accuracy averaged 0.35 for Angus with a range from 0.33 (REA) to 0.39 (CMAR) and averaged 0.33 for Charolais with a range from 0.18 (REA) to 0.46 (AFAT). The prediction accuracy was slightly higher on average when the data were split by animal's birth year than when the data were split by sire family. These results demonstrate that the genetic relationship or relatedness of selection candidates with the training population has a great impact on the accuracy of predicting genomic breeding values under the density of the marker panel used in this study.     

Divergent growth of Norway spruce on Babia Góra Mountain in the western Carpathians

Growth divergence – i.e. the expression of divergent growth trends of neighboring trees – has certain implications for dendrochronological research, for instance in the context of climate reconstructions but also in terms of estimating net ecosystem productivity. Thus, understanding the underlying mechanisms is essential to extend our fundamental dendroecological knowledge. In this context, the Picea genus plays an important role since several of its species were reported to exhibit growth divergence. Here, we investigate a well sampled Norway spruce (Picea abies (L.) Karst) data set for growth divergence comprising ring-width and Blue Intensity measurements from seven sites on Babia Góra Mountain, at the border between Poland and Slovakia. By means of Principal Component Gradient Analysis, inter-series correlations, and climate growth relationships, we are able to show that I) Norway spruce on Babia Góra expressed growth divergence since the 1970s, II) the definition of groups increased the strength of population signals and the stability of climate-growth relationships, and III) Blue Intensity appeared as a more robust proxy for environmental conditions. We discuss soil heterogeneity, genetics, and air pollution as possible underlying mechanisms, thereby indicating further research avenues to obtain a better understanding of growth divergence.     

Coping with drought: diapause plasticity in katydid eggs at high,mid-, and low elevations

1. Semi-arid rangeland productivity is limited by precipitation, and yet droughts are projected to increase in frequency and duration with unknown impacts on insect populations. As some katydids prolong diapause and remain in an egg bank as a blastoderm for multiple growing seasons, is it possible that drought could prolong diapause and promote outbreaks by synchronising embryonic development and hatching of Mormon crickets, Anabrus simplex, after moisture is restored? 2. In this study, a high-elevation Wyoming population (WY) was compared with a mid-elevation Idaho (ID) and a low-elevation Oregon population (OR). It was predicted that eggs from the drier ID and OR habitats would be more tolerant of desiccation. Developmental state and water loss of eggs were measured after drought treatments, and when moisture was restored. 3. The two drier treatments had significantly more WY eggs prolonging diapause until after drought ended compared with the two wetter treatments. Whether WY eggs developed in the second or subsequent warm periods was independent of drought treatments. Significantly fewer OR embryos developed in the driest treatment compared with the others, whereas almost all ID eggs developed irrespective of the drought treatment. 4. In conclusion, Mormon crickets can delay embryonic development to improve drought tolerance. Although drought did not synchronise development and hatching, diapause plasticity allowed insects to cope and await more favourable conditions. 5. Unexpectedly, eggs from WY (the highest, wettest site) were more tolerant, because postponing development resulted in less water loss than in developed embryos. OR egg loss was also reduced by prolonging diapause, relative to ID, which developed in even the driest conditions.     

The influence of age and sex on phagocyte chemiluminescence

The process of ageing is associated with increased susceptibility to infection. Phagocytes form the primary defence mechanism against infecting microorganisms, but the influence of ageing on phagocyte function remains controversial. In this study we have applied a microtitre plate phagocyte chemiluminescence (CL) assay suitable for clinical use to compare phagocyte oxidative metabolism in younger healthy subjects (age 20–60 years) and healthy older (60–70 years) subjects. Polymorphonuclear leukocytes (PMNL) and monocytes were stimulated using phorbol myristate acetate (PMA), serum opsonized zymosan (SOZ), and non-opsonized zymosan (ZYM) in the presence of both lucigenin and luminol. Monocytes showed a higher luminolenhanced CL response to PMA in males compared with females in the younger age group. No PMNL differences were observed between the sexes. Although no difference were found in relation to age when cells were stimulated with PMA and SOZ, significantly lower background (unstimulated) CL was obtained from PMNL with luminol. PMNL luminol-enhanced CL responses were also lower in response to ZYM. The findings suggest a reduced response of PMNL from older subjects to minimal stimulation. This could be related to abnormalities in the triggering of the respiratory burst or myeloperoxidase release due to ageing. The influence of age and sex should be taken into account in clinical studies of phagocyte CL.     

气候变化下中国八种梧桐属树种潜在适生区模拟

中国梧桐属（Firmiana）在世界梧桐属中占比较大，且除梧桐外其余种均为中国特有且分布范围狭窄的植物种，灭绝风险大，研究气候变化对中国梧桐属树种的影响对于维护生物多样性具有重要的意义。结合多时期第六次国际气候耦合模式比较计划（CMIP6）气候变量数据和中国八种梧桐属树种的分布数据，基于R语言kuenm程序包优化的最大熵（Maxent）模型模拟分析中国八种梧桐属树种在多尺度下的潜在适生区，得出梧桐属最适宜的模拟尺度、潜在适生区的面积变化和迁移方向、梧桐属多样性保护关键区域及保护空缺。结果表明：（1）梧桐属最适宜的模拟尺度为亚洲；（2） Maxent模型的接收者操作特征曲线下面积（AUC）值均大于0.9，表明模型对梧桐属潜在适生区预测结果具有较高准确度；（3）气候变化影响下除云南梧桐（Firmiana major）外其它树种的潜在适生区都将在未来有所扩大；（4）中国八种梧桐属树种潜在适生区迁移方向主要为东西向，南北向大跨度迁移较少，纬度变化不大；（5）丹霞梧桐（Firmiana danxiaensis）的稳定潜在适生区最小；（6）中国梧桐属多样性保护关键区域主要分布于广西壮族自治区及云南、广东、海南等省区；（7）中国梧桐属多样性保护空缺区域主要分布于广西壮族自治区中部及海南省北部；（8）梧桐属多样性保护关键区域正在为人造地表所侵蚀。研究分析气候变化对中国八种梧桐属树种的影响及其潜在适生区变化、中国梧桐属多样性保护状态，可为中国梧桐属建立多样性保护廊道提供相关建议，为制定多样性保护规划及相应措施提供参考。     

Testing prediction accuracy in short-term ecological studies

Applied ecology is based on an assumption that a management action will result in a predicted outcome. Testing the prediction accuracy of ecological models is the most powerful way of evaluating the knowledge implicit in this cause-effect relationship, however, the prevalence of predictive modeling and prediction testing are spreading slowly in ecology. The challenge of prediction testing is particularly acute for small-scale studies, because withholding data for prediction testing (e.g., via k-fold cross validation) can reduce model precision. However, by necessity small-scale studies are common. We use one such study that explored small mammal abundance along an elevational gradient to test prediction accuracy of models with varying degrees of information content. For each of three small mammal species, we conducted 5000 iterations of the following process: (1) randomly selected 75 % of the data to develop generalized linear models of species abundance that used detailed site measurements as covariates, (2) used an information theoretic approach to compare the top model with detailed covariates to habitat type-only and null models constructed with the same data, (3) tested those models’ ability to predict the 25 % of the randomly withheld data, and (4) evaluated prediction accuracy with a quadratic loss function. Detailed models fit the model-evaluation data best but had greater expected prediction error when predicting out-of-sample data relative to the habitat type models. Relationships between species and detailed site variables may be evident only within the framework of explicitly hierarchical analyses. We show that even with a small but relatively typical dataset (n = 28 sampling locations across 125 km over two years), researchers can effectively compare models with different information content and measure models’ predictive power, thus evaluating their own ecological understanding and defining the limits of their inferences. Identifying the appropriate scope of inference through prediction testing is ecologically valuable and is attainable even with small datasets.     

Reprogramming of Stem Cell Activity to Convert Thorns into Branches

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