Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments

The advent of rapid complete genome sequencing, and the potential to capture this information in genome-scale metabolic models, provide the possibility of comprehensively modeling microbial community interactions. For example, Rhodoferax and Geobacter species are acetate-oxidizing Fe(III)-reducers that compete in anoxic subsurface environments and this competition may have an influence on the in situ bioremediation of uranium-contaminated groundwater. Therefore, genome-scale models of Geobacter sulfurreducens and Rhodoferax ferrireducens were used to evaluate how Geobacter and Rhodoferax species might compete under diverse conditions found in a uranium-contaminated aquifer in Rifle, CO. The model predicted that at the low rates of acetate flux expected under natural conditions at the site, Rhodoferax will outcompete Geobacter as long as sufficient ammonium is available. The model also predicted that when high concentrations of acetate are added during in situ bioremediation, Geobacter species would predominate, consistent with field-scale observations. This can be attributed to the higher expected growth yields of Rhodoferax and the ability of Geobacter to fix nitrogen. The modeling predicted relative proportions of Geobacter and Rhodoferax in geochemically distinct zones of the Rifle site that were comparable to those that were previously documented with molecular techniques. The model also predicted that under nitrogen fixation, higher carbon and electron fluxes would be diverted toward respiration rather than biomass formation in Geobacter, providing a potential explanation for enhanced in situ U(VI) reduction in low-ammonium zones. These results show that genome-scale modeling can be a useful tool for predicting microbial interactions in subsurface environments and shows promise for designing bioremediation strategies.     

Signaling-mediated cross-talk modulates swarming and biofilm formation in a coral pathogen Serratia marcescens

Interactions within microbial communities associated with marine holobionts contribute importantly to the health of these symbiotic organisms formed by invertebrates, dinoflagellates and bacteria. However, mechanisms that control invertebrate-associated microbiota are not yet fully understood. Hydrophobic compounds that were isolated from surfaces of asymptomatic corals inhibited biofilm formation by the white pox pathogen Serratia marcescens PDL100, indicating that signals capable of affecting the associated microbiota are produced in situ. However, neither the origin nor structures of these signals are currently known. A functional survey of bacteria recovered from coral mucus and from cultures of the dinoflagellate Symbiodinium spp. revealed that they could alter swarming and biofilm formation in S. marcescens. As swarming and biofilm formation are inversely regulated, the ability of some native α-proteobacteria to affect both behaviors suggests that the α-proteobacterial signal(s) target a global regulatory switch controlling the behaviors in the pathogen. Isolates of Marinobacter sp. inhibited both biofilm formation and swarming in S. marcescens PDL100, without affecting growth of the coral pathogen, indicative of the production of multiple inhibitors, likely targeting lower level regulatory genes or functions. A multi-species cocktail containing these strains inhibited progression of a disease caused by S. marcescens in a model polyp Aiptasia pallida. An α-proteobacterial isolate 44B9 had a similar effect. Even though ∼4% of native holobiont-associated bacteria produced compounds capable of triggering responses in well-characterized N-acyl homoserine lactone (AHL) biosensors, there was no strong correlation between the production of AHL-like signals and disruption of biofilms or swarming in S. marcescens.     

Net annual global warming potential and greenhouse gas intensity in Chinese double rice‐cropping systems: a 3‐year field measurement in long‐term fertilizer experiments

The impact of agricultural management on global warming potential (GWP) and greenhouse gas intensity (GHGI) is not well documented. A long‐term fertilizer experiment in Chinese double rice‐cropping systems initiated in 1990 was used in this study to gain an insight into a complete greenhouse gas accounting of GWP and GHGI. The six fertilizer treatments included inorganic fertilizer [nitrogen and phosphorus fertilizer (NP), nitrogen and potassium fertilizer (NK), and balanced inorganic fertilizer (NPK)], combined inorganic/organic fertilizers at full and reduced rate (FOM and ROM), and no fertilizer application as a control. Methane (CH₄) and nitrous oxide (N₂O) fluxes were measured using static chamber method from November 2006 through October 2009, and the net ecosystem carbon balance was estimated by the changes in topsoil (0–20 cm) organic carbon (SOC) density over the 10‐year period 1999–2009. Long‐term fertilizer application significantly increased grain yields, except for no difference between the NK and control plots. Annual topsoil SOC sequestration rate was estimated to be 0.96 t C ha^?1 yr^?1 for the control and 1.01–1.43 t C ha^?1 yr^?1 for the fertilizer plots. Long‐term inorganic fertilizer application tended to increase CH₄ emissions during the flooded rice season and significantly increased N₂O emissions from drained soils during the nonrice season. Annual mean CH₄ emissions ranged from 621 kg CH₄ ha^?1 for the control to 1175 kg CH₄ ha^?1 for the FOM plots, 63–83% of which derived from the late‐rice season. Annual N₂O emission averaged 1.15–4.11 kg N₂O–N ha^?1 in the double rice‐cropping systems. Compared with the control, inorganic fertilizer application slightly increased the net annual GWPs, while they were remarkably increased by combined inorganic/organic fertilizer application. The GHGI was lowest for the NP and NPK plots and highest for the FOM and ROM plots. The results of this study suggest that agricultural economic viability and GHGs mitigation can be simultaneously achieved by balanced fertilizer application.     

以技术为主线开设药学类专业微生物学综合实验

以技术为主线开设药学类专业微生物学综合实验,能够帮助药学专业的学生更好地掌握微生物最基本的操作技能,了解微生物实验的基本流程,加深对微生物知识的理解,增强学习兴趣和创新能力,培养出药学微生物生产实践、教学科研全面的人才。     

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model‐data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter‐model variation is generally large and model agreement varies with timescales. In severely water‐limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily–monthly) timescales and reduces on longer (seasonal–annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter‐model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.     

Plant community composition steers grassland vegetation via soil legacy effects

Soil legacy effects are commonly highlighted as drivers of plant community dynamics and species co‐existence. However, experimental evidence for soil legacy effects of conditioning plant communities on responding plant communities under natural conditions is lacking. We conditioned 192 grassland plots using six different plant communities with different ratios of grasses and forbs and for different durations. Soil microbial legacies were evident for soil fungi, but not for soil bacteria, while soil abiotic parameters did not significantly change in response to conditioning. The soil legacies affected the composition of the succeeding vegetation. Plant communities with different ratios of grasses and forbs left soil legacies that negatively affected succeeding plants of the same functional type. We conclude that fungal‐mediated soil legacy effects play a significant role in vegetation assembly of natural plant communities.     

268份人类免疫缺陷病毒抗体待确定样本的检测结果分析

为了提高实验室人类免疫缺陷病毒(human immunodeficiency virus,HIV)抗体检测能力及对免疫蛋白印迹(Western blot,WB)实验结果的判断能力,对送检至北京市东城区艾滋病确证实验室的268份HIV抗体待确定样本进行确证实验及结果分析。按照试剂说明书和实验室标准作业程序(Standard Operation Procedure,SOP)操作对送检的全部样本进行WB确证实验;了解HIV筛查实验结果与确证实验结果的相关性,并分析不同送检机构、送检人群样本的检测结果差异以及不同试剂、不同检测方法的结果差异。结果显示在筛查出抗体待确定的268份样本中,确证阳性170份,阳性率63.43%;确证阴性51份,阴性率19.03%;不确定结果47份,占筛查有反应的17.54%。确证阳性病例来自监管场所、自愿咨询检测门诊(Voluntary Counseling and Test,VCT)和医疗机构,不同送检单位及不同人群的阳性样本率有显著统计学意义(P<0.01)。WB确证阳性样本带型以全条带和次全条带为主,且所有确证阳性标本均来自双试剂阳性样本。不同检测方法阳性样本率的差异有显著统计学意义(P<0.01),其中化学发光法的样本阳性率占46.27%,酶联免疫吸附实验(ELISA)占88.29%,胶体硒法占43.48%。本研究结果提示,对潜在HIV感染者,应扩大检测面,加强医疗机构检测,并提供一种以上方法的多次检测,以减少漏检的风险。     

松籽油的干式酶法提取工艺优化与理化性质分析

应用单因素实验设计对干式酶法松籽油提取工艺进行优化。结果表明,干式酶法提取松籽油最佳制备工艺为：0.2%淀粉酶、料液比为6：1、酶解温度为55℃、酶解时间为8 h,所得最大出油率为90.2%,残油率为6.2%。经检测最佳制备条件提取的松籽油不饱和脂肪酸的含量为90.09%,其中油酸含量为26.84%,介酸含量为2.41%、亚油酸含量为46.25%、皮诺敛酸为14.59%;饱和脂肪酸中棕榈酸含量为6.5%、硬脂酸为3.41%。松籽油酸价为2.61 mg·g^-1、过氧化值为1.56 mmol·kg^-1、丙二醛含量为0.41 mg·kg^-1。所有检测结果均高于《中华人民共和国粮食行业标准LS/T 3242-2014》松籽油中质量标准的要求。