柴油降解基因工程菌的构建及降解特性

【目的】构建柴油降解基因工程菌,提高柴油降解速率,研究p450基因在柴油降解过程中的作用。【方法】将Alcanivorax borkumensis SK2的p450基因合成后,连接至烷烃响应表达载体p Com8中,构建该基因的表达载体p450-SK2/p Com8,并将其转入大肠杆菌DH5α中,通过SDS-PAGE检测该基因在大肠杆菌DH5α中的表达,并将重组质粒p450-SK2/p Com8转入柴油降解菌Acinetobacter sp.Y9中,构建基因工程菌p450-SK2/Y9,研究工程菌p450-SK2/Y9对柴油的降解特性及p450基因在构建的工程菌p450-SK2/Y9中的表达。【结果】PCR、酶切及测序结果表明重组质粒p450-SK2/p Com8构建正确。当柴油诱导浓度大于1%时,目的基因在大肠杆菌DH5α中的蛋白表达量较大,且随着诱导时间的延长而呈增加趋势。通过PCR检测构建的基因工程菌p450-SK2/Y9中的p450基因表明,工程菌构建正确,利用单菌株降解柴油时,宿主菌Y9与工程菌p450-SK2/Y9的柴油降解效率未见明显差异,但工程菌p450-SK2/Y9在构建的菌群中对柴油降解的促进效果明显。SDS-PAGE结果表明,p450基因在构建的工程菌p450-SK2/Y9中能得到准确表达,在混合菌中的表达量高于单菌株。【结论】柴油降解基因工程菌在混合菌群中对柴油降解具有促进作用,而在单菌株情况下未见促进作用,且p450基因的蛋白表达在混合菌中也高于单菌株,这对于提高柴油的降解速率及研究p450基因在柴油降解过程中的作用机理具有一定意义。     

悦目金蛛拖丝的超微结构研究

采用非固定的抽丝方法,从一只未麻醉的悦目金蛛(Argiope amoena)的纺器将拖丝抽出,然后用扫描电镜(SEM)对拖丝进行超微结构的观察,结果表明:悦目金蛛拖丝至少具有2根、3根、4根及多根单丝纤维构成的4种不同结构,其中有一种类似弹簧的结构;另外,丝的表面还出现一种小环结构,这两种结构可能是拖丝纤维具有优良机械性能的原因之一。"束状结构"和"小环结构"在文献中未见报道。拖丝的直径范围为0.25~10.77μm;悦目金蛛似乎能调节拖丝的结构和直径,以适应其所面临的即时环境。本文基于上述观察结果并结合前人的研究,提出了蜘蛛拖丝结构-生物学功能多样性假说,对蜘蛛丝的结构与生物学功能之间的关系作了探讨。     

DLGCN:基于图卷积网络的药物-lncRNA[]关联预测

为实现高通量识别新的药物-长链非编码RNA(Long non-coding RNA, lncRNA)关联,本文提出了一种基于图卷积网络模型来识别潜在药物-lncRNA关联的方法DLGCN(Drug-LncRNA graph convolution network)。首先,基于药物的结构信息和lncRNA的序列信息分别构建了药物-药物和lncRNA-lncRNA相似性网络,并整合实验证实的药物-lncRNA关联构建了药物-lncRNA异质性网络。然后,将注意力机制和图卷积运算应用于该网络中,学习药物和lncRNA的低维特征,基于整合的低维特征预测新的药物-lncRNA关联。通过效能评估,DLGCN的受试者工作特性曲线下面积(Area under receiver operating characteristic, AUROC)达到0.843 1,优于经典的机器学习方法和常见的深度学习方法。此外,DLGCN预测到姜黄素能够调控lncRNA MALAT1的表达,已被最近的研究证实。DLGCN能够有效预测药物-lncRNA关联,为肿瘤治疗新靶点的识别和抗癌药物的筛选提供了重要参考。     

呼肠病毒BYD株吸附蛋白σ1的原核表达及其抗原性鉴定

将呼肠病毒BYD株S1片段编码的细胞吸附蛋白基因连接至pET-28a( ),构建表达载体pET-28a( )-S1,转化表达宿主菌E.coli BL21(DE3),分析表达载体能否表达预期大小的重组σ1,并进一步鉴定重组σ1的抗原性。SDS-PAGE实验表明,经IPTG诱导后,表达载体能表达53kD左右蛋白质,与重组σ1的预期大小相符;免疫印迹分析表明重组σ1有较好的抗原性和特异性,可用于呼肠病毒诊断试剂的制备。     

农田小麦在土壤湿润条件下的气孔活动

1984年在北京大屯农业生态系统试验站用MK 3型自动气孔计对土壤湿润、睛朗天气条件下冬小麦气孔传导力的日变化,季节变化、以及叶龄和梯度变化进行了观测。发现叶片传导力(gl)的日变化为双峰曲线,正午gl的降低可能是强光和高的饱和差作用的结果,从而限制了光合潜力的发挥。近轴面传导力(gd)和远轴面传导力(gb)的比(α)不是一个常数,这是因为两面气孔对环境条件的反应不同。gl和冠层传导力(g(?))都以孕穗期为最高。灌浆时期gl和gc有所降低,反映了叶片的过早衰老。这是影响本地区小麦产量的重要因素之一,其原因不仅与土壤水分有关,还与大气条件和病虫害有关。本文还讨论了gl随时龄的变化。观测表明,气孔计可以迅速准确地掌握作物群体的生理动态,有可能用于指导农田灌灌和管理。     

基于人工掩蔽物法的若尔盖湿地中华蟾蜍种群生态研究

近几十年来,全球两栖动物种群衰减显著,两栖动物的生存现状引起了越来越多的生态学家和保护生物学家的关注。若尔盖湿地不仅是世界上最大的一块高原泥炭沼泽湿地,也是我国生物多样性保护的热点地区之一。该地区分布有3种两栖类:高原林蛙(Rana kukunoris)、倭蛙(Narorana pleskei)和中华蟾蜍岷山亚种(Bufo gargarizans minshanica)。已有研究发现该3种两栖动物种群数量均有不同程度的下降。采用人工掩蔽物法,在2011—2014年对该地区中华蟾蜍种群生态做了连续追踪。结果表明:该区域中华蟾蜍种群数量逐年波动较大,年龄结构数据显示该种群处于增长期;中华蟾蜍为聚集分布,且发现率与水体距离呈显著的线形关系(P0.01),在样地范围内离水体越远,发现的个体越多;线形样方比方形样方捕获动物的效率更高(P=0.018);中华蟾蜍亚成体的肥满度季节间无明显差异;中华蟾蜍具有较强的迁徙能力,可能沿着固定的线路周而复始的迁徙。对于家域范围大,迁徙距离远的中华蟾蜍这类物种,应加强最适栖息地的保护并防止栖息地破碎化。     

基于湿度分布特征的小尺度土壤碳通量空间采样策略

由于土壤碳通量的空间异质性很强,传统的随机抽样方法无法对区域土壤碳通量进行准确估算,而多点采样需耗费大量的人力及设备成本,因此确定适当的采样点数量及分布策略对于区域土壤碳通量的测算非常重要。提出一种基于湿度空间分布特征的小尺度土壤碳通量空间采样策略:首先利用无线传感网密集测量区域的土壤湿度,根据湿度数据的空间分布特征划分监测区域,通过Hammond Mc Cullagh方程计算各子区域内的最优采样点数量,最终确定整个监测区域的空间采样点部署策略。提出的方法考虑了各子区域间土壤碳通量空间分布的差异,使得采样点的部署位置与土壤碳通量的分布具有较好的相关性。研究结果证明:土壤碳通量部署策略能够获得比均匀部署策略、随机部署策略更高的区域土壤碳通量估算准确度。     

内蒙古土地利用变化对生态系统防风固沙功能的影响

土壤风蚀是内蒙古的严重环境问题之一。在对内蒙古2000年到2010年的土地利用变化特征进行分析的基础上,分析了内蒙古土地利用变化的主要特征,以RWEQ模型估算了内蒙古2000年和2010年的固沙物质量,采用空间统计分析评估了固沙功能对土地利用变化的响应,结果表明:(1)2000—2010年土地利用变化以城镇高速发展、草地和湿地面积锐减、林地灌丛有所恢复以及荒漠环境改善为主要特征。(2)2000—2010的十年间内蒙古固沙物质总量增长了17.75%,草地总面积虽有所降低,但是部分区域草地覆盖度的上升增强了草地固沙能力,而林地的固沙物质量则由于农田、草地改为林地的短期内地表保护力的下降而有所降低。(3)十年间农田退耕还草、荒漠环境的改善、草地质量提高等土地利用变化方式有益于生态环境质量的提高,使生态防风固沙功能得以增强,造成固沙物质量提高了约0.25亿t。(4)农田开垦、城镇发展、荒漠化发展、湿地萎缩以及草地的退化等土地利用变化会使生态环境质量降低,生态系统防风固沙功能下降,累计造成的固沙物质量的减少总量约为0.19亿t。从十年间综合来看,内蒙古的土地利用变化对区域固沙功能有一定的增强作用,但是尚存在城镇发展过快、草地湿地转化压力过大、草地退化、荒漠化对固沙功能的弱化问题,需要在今后的土地利用规划和管理工作中予以改进以进一步增强区域固沙功能,构建北方地区生态安全屏障。     

Association between long-term exposure to ambient air pollution and COVID-19 severity: a prospective cohort study

Background:The tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system.Methods:We used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and ground-level ozone (O₃), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals’ long-term exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage.Results:Among the 151 105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM_2.5 (1.70 μg/m³), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01–1.12), 1.09 (95% CI 0.98–1.21) and 1.00 (95% CI 0.90–1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO₂. We also estimated odds ratios of 1.15 (95% CI 1.06–1.23), 1.30 (95% CI 1.12–1.50) and 1.18 (95% CI 1.02–1.36) per interquartile range increase of 5.14 ppb in O₃ for hospital admission, ICU admission and death, respectively.Interpretation:Chronic exposure to air pollution may contribute to severe outcomes after SARS-CoV-2 infection, particularly exposure to O₃.

By November 2021, COVID-19 had caused more than 5 million deaths globally¹ and more than 29 400 in Canada.² The clinical manifestations of SARS-CoV-2 infection range from being asymptomatic to multiple organ failure and death. Identifying risk factors for COVID-19 severity is important to better understand etiological mechanisms and identify populations to prioritize for screening, vaccination and medical treatment. Risk factors for severity of COVID-19 include male sex, older age, pre-existing medical conditions and being from racialized communities.^3–5 More recently, ambient air pollution has been implicated as a potential driver of COVID-19 severity.^6–10Long-term exposure to ambient air pollution, a major contributor to global disease burden,¹¹ could increase the risk of severe COVID-19 outcomes by several mechanisms. Air pollutants can reduce individuals’ pulmonary immune responses and antimicrobial activities, boosting viral loads.⁸ Air pollution can also induce chronic inflammation and overexpression of the alveolar angiotensin-converting enzyme 2 (ACE) receptor,⁷ the key receptor that facilitates SARS-CoV-2 entry into cells.^12,13 Exposure to air pollution contributes to chronic conditions, such as cardiovascular disease, that are associated with unfavourable COVID-19 prognosis, possibly owing to persistent immune activation and excessive amplification of cytokine development.¹⁰ Thus, greater exposure to long-term air pollution may lead to severe COVID-19 outcomes.Reports exist of positive associations between long-term exposure to particulate matter with diameters equal to or smaller than 2.5 or 10 μm (PM_2.5 and PM₁₀), ground-level ozone (O₃) and nitrogen dioxide (NO₂), and metrics of COVID-19 severity (e.g., mortality and case fatality rate).^8–10 However, most studies to date have used ecological and cross-sectional designs, owing to limited access to individual data, which leads to ambiguity in interpreting the results, thus hindering their influence on policy. ^6,14 Ecological designs do not allow for disentangling the relative impacts of air pollution on individual susceptibility to infection and disease severity.¹⁴ Residual confounding by factors such as population mobility and social interactions is also problematic. Therefore, a cohort study with data on individuals with SARS-CoV-2 is a more appropriate design.^6,14 Studies that have used individual data were conducted in specific subpopulations^15,16 or populations with few severe cases,¹⁷ or had limited data on individual exposure to air pollutants.¹⁸ In Canada, 1 ecological study found a positive association between long-term exposure to PM_2.5 and COVID-19 incidence,¹⁹ but no published study has explored the association between air pollution and COVID-19 severity.We aimed to examine the associations between long-term exposure to 3 common air pollutants (PM_2.5, NO₂ and O₃) and key indicators of COVID-19 severity, including hospital admission, intensive care unit (ICU) admission and death, using a large prospective cohort of people with confirmed SARS-CoV-2 infection in Ontario, Canada, in 2020. The air contaminants PM_2.5, NO₂ and O₃ are regularly monitored by the Canadian government, and are key pollutants that are considered when setting air-quality policies. They originate from varying sources (NO₂ is primarily emitted during combustion of fuel, O₃ is primarily formed in air by chemical reactions of nitrogen oxides and volatile organic compounds, and PM_2.5 can be emitted during combustion or formed by reactions of chemicals like sulphur dioxide and nitrogen oxides in air) and they may affect human health differently.^20,21,22     

谭清苏铁性别相关的RAPD标记研究

以谭清苏铁(Cycas tanqingii D.Y.Wang)雌雄植株半年生羽叶为材料,用优化的CTAB法分别提取其全基因组DNA,进行RAPD单因子梯度实验和正交实验以优化扩增条件。应用160个RAPD随机引物检测基因组DNA,雌雄植株均扩增出1450多条带,其中引物S0465扩增出与谭清苏铁雌株高度相关的RAPD标记,其大小约为500bp,该标记与雄株没有关联。