您选择的条件: 微生物学(4)
  • Metagenomic evidence for the coexistence of SARS and H1N1 in patients from 2007-2012 flu seasons

    分类: 生物学 >> 微生物学 分类: 医学、药学 >> 基础医学 提交时间: 2021-08-11

    摘要: By re-analzying public metagenomic data from 101 patients infected with influenza A virus during the 2007-2012 H1N1 flu seasons in France, we identified 22 samples with SARS-CoV sequences. In 3 of them, the SARS genome sequences could be fully assembled out of each. These sequences are highly similar (99.99% and 99.7%) to the artificially constructed recombinant 5 SARS-CoV (SARSr-CoV) strains generated by the J. Craig Venter Institute in USA. Moreover, samples from different flu seasons have different SARS-CoV strains, and the divergence between these strains cannot be explained by natural evolution. Our study also shows that retrospective studies using public metagenomic data from past major epidemic outbreaks serves as a genomic strategy for the research of origins or spread of infectious diseases.

  • 塔里木河下游柽柳灌丛土壤真菌群落结构及多样性分析

    分类: 生物学 >> 微生物学 提交时间: 2021-06-17 合作期刊: 《干旱区地理》

    摘要: 土壤真菌群落对干旱区土壤生态系统功能的维持具有重要作用。为研究新疆干旱地区柽 柳沙包和非沙包土壤理化性质对土壤真菌群落结构的影响,该实验采集了塔里木河下游英苏断面附近沙包柽柳灌丛和非沙包柽柳灌丛的冠幅内部、冠幅边缘和灌丛边缘 3 个位置的土壤,基于高通量测序对沙包柽柳灌丛和非沙包柽柳灌丛土壤真菌群落结构及功能进行初步研究,结合土壤理化 性质,分析沙包和土壤因素对土壤真菌群落结构和功能的综合影响。结果表明:(1)土壤 pH、速效钾、全钾、铵态氮、速效磷在柽柳灌丛的不同位置存在显著性差异,而土壤含水量、电导率、总盐、有 机质、全氮、全磷、硝态氮在整个柽柳灌丛中均无显著性差异。(2)该区域柽柳灌丛土壤真菌分为 1 界,14 门,48 纲,110 目,227 科,410 属,557 种。在门水平上,子囊菌门、担子菌门和被孢霉门为该区域柽柳灌丛主要的优势菌门,在属水平上,链格孢属、曲霉属、Stolonocarpus、刺盘孢属、unidenti⁃fied_Saccharomycetales_sp、裸子囊菌属为柽柳灌丛的主要优势菌属。(3)通过分析土壤理化因子与土壤真菌群落的关系,发现全氮、速效钾、铵态氮是影响土壤真菌群落结构的主要环境因子,全磷与曲霉属、Microthelia、裸子囊菌属、Phialosimplex 均呈显著正相关关系,全氮与链格孢属呈显著正 相关关系。(4)基于 FUNGuild 真菌功能预测,在柽柳灌丛中共检测到腐生、共生、病理 3 类营养型和 5 类互有交叉营养型功能菌群,其中腐生营养型(30.0%)功能真菌在柽柳灌丛中占据主导优势,其 次是病理-腐生-共生营养型(10.6%)、病理-共生营养型(5.9%)、共生营养型(4.3%)在柽柳灌丛中 占据一定的优势。(5)研究发现柽柳沙包和柽柳冠幅对土壤养分和土壤真菌的富集效应不明显,但在沙包冠幅内功能真菌与其它组存在明显差异,说明柽柳灌丛沙包和冠幅的综合效对土壤真菌功能组成有较大的影响。

  • 塔里木河下游胡杨根际土壤细菌群落多样性分析

    分类: 生物学 >> 微生物学 提交时间: 2021-06-17 合作期刊: 《干旱区地理》

    摘要: 采用高通量测序技术,对塔里木河下游不同生长时期(幼龄期、中壮期、过熟期、衰亡期)胡 杨根际土壤细菌进行测序,结合典范对应分析(CCA)与 Spearman 相关性分析,探讨细菌群落组成 与环境因子的相关性。结果表明:(1)土壤样品共获得 7287 个操作分类单元(OTUs),经过对比鉴 定共得到 73 门,165 纲,339 目,454 科,651 属和 205 种。(2)胡杨根际土壤细菌群落丰富度和多样性 随生长时期表现为先增加后降低的趋势,而不同生长时期间无显著差异。(3)胡杨根际细菌群落主 要的优势细菌门为变形菌门(Proteobacteria)、unidentified_Bacteria、Halobacterota,优势细菌属为海 杆菌属(Marinobacter)、嗜盐单胞菌属(Halomonas)、Woeseia,相较于门分类学水平,细菌群落组成在 属水平上存在较大差异,不同生长时期胡杨根际细菌群落的优势菌属不同。(4)不同生长时期胡杨根际土壤细菌群落组成可分为两大类,中壮期与衰亡期的土壤样品聚为一类,幼龄期与过熟期的 土壤样品聚为一类。(5)CCA 分析表明土壤含水量、全钾、总盐、pH 是显著影响胡杨根际土壤细菌 群落组成的环境因子(P<0.05)。研究结果为丰富干旱区根际微生物的研究、探讨干旱区植物-微 生物之间的相互作用提供科学依据。

  • Comparing lethal dose ratios using probit regression with arbitrary slopes

    分类: 生物学 >> 微生物学 提交时间: 2018-11-26

    摘要:Background: Evaluating the toxicity or effectiveness of two or more toxicants in a specific population often requires specialized statistical software to calculate and compare median lethal doses (LD50s). Tests for equality of LD50s using probit regression with parallel slopes have been implemented in many software packages, while tests for cases of arbitrary slopes are not generally available. Methods: In this study, we established probit-log(dose) regression models and solved them by the maximum likelihood method using Microsoft Excel. The z- and χ2-tests were used to assess significance and goodness of fit to the probit regression models, respectively. We calculated the lethal doses (LDs) of the toxicants at different significance levels and their 95% confidence limits (CLs) based on an accurate estimation of log(LD) variances. We further calculated lethal dose ratios and their 95% CLs for two examples without assuming parallel slopes following the method described by Robertson, et al., 2017. Results: We selected representative toxicology datasets from the literature as case studies. For datasets without natural responses in the control group, the slopes, intercepts, χ2 statistics and LDs calculated using our method were identical to those calculated using Polo-Plus and SPSS software, and the 95% CLs of the lethal dose ratios between toxicants were close to hose calculated using Polo-Plus. For datasets that included natural responses in the control group, our results were also close to those calculated using Polo-Plus and SPSS. Conclusion: This procedure yielded accurate estimates of lethal doses and 95% CLs at different significance levels as well as the lethal dose ratios and 95% CLs between two examples. The procedure could be used to assess differences in the toxicities of two examples without the assumption of parallelism between probit-log(dose) regression lines.