全国大学生生命科学竞赛数据分析与展望

全国大学生生命科学竞赛至今已举办三届,赛事组织好、规模大、参与度高,对促进生命科学教育与研究具有重要作用。文中简述全国大学生生命科学竞赛的模式与现状,并基于前三届竞赛数据分地区分年度统计分析报名数据和竞赛成绩,同时结合生命科学领域的新变化新认识进行展望,以更好地推动赛事发展。     

军曹鱼催乳素受体PRLR1基因的克隆及其在不同盐度条件下mRNA表达差异

催乳素受体通过结合催乳素,能调节鱼体渗透压。为研究催乳素受体1(PRLR1)在高盐水体和低盐水体中对军曹鱼(Rachycentron canadum)的渗透调节作用,利用cDNA末端快速扩增(RACE-PCR)技术,获得了军曹鱼PRLR1全长cDNA序列。该基因全长为2629 bp,包含1953 bp的开放阅读框ORF,可编码650个氨基酸。氨基酸序列包含了2个纤维连接蛋白3型结构域(FN3)、保守的WS区和box1。采用qRT-PCR技术,检测不同盐度(10‰、30‰和35‰)条件下鳃、肠、体肾中PRLR1基因mRNA表达情况。结果显示,PRLR1基因在军曹鱼的各个组织中均有表达,其中鳃表达量最高,其次是肌肉、体肾和肠,而在胃、脾、脑和心脏中则微量表达。低盐组、正常组和高盐组中,PRLR1基因的表达量均为鳃最高;肠次之;体肾最低。随着盐度提高,PRLR1基因的鳃、肠和体肾组织表达量变化规律均呈逐步下降趋势。以上结果反映了军曹鱼PRLR1在渗透压器官中的功能差异性,说明PRLR1在军曹鱼渗透压调节上具有重要作用。     

气候变化和经济发展对肾综合征出血热发生的影响

肾综合征出血热(hemorrhagic fever with renal syndrome, HFRS)是一种啮齿动物传播的自然疫源性疾病, 危害严重, 已成为全球重要的公共卫生问题。本研究采用数理统计模型及小波分析方法, 对陕西省西安市鄠邑区1984-2016年HFRS的发生与鼠类、气候和经济因素的关系进行分析, 探讨气候和经济因素对HFRS发生的影响。小波分析结果表明, 该地区的HFRS暴发史可能分为两个时期, 推测每个时期具有不同的主要宿主, 在2002年褐家鼠(Rattus norvegicus)可能取代黑线姬鼠(Apodemus agrarius)成为HFRS疫源地的主要宿主。广义可加模型模拟结果表明, HFRS的发生与1984-2001年黑线姬鼠密度间存在极显著非线性效应(F_2.06,9.02 = 102.415, P < 0.01), 两者间显现为正相关; 与2002-2016年的褐家鼠密度间呈正相关(F_1.67,9.02 = 73.929, P < 0.01); HFRS主要宿主的这种变化可能与当地气候变化和经济发展有关: HFRS的发生与年平均温度存在极显著的非线性效应(F_2.93,9.02 = 12.164, P < 0.01), 两者间呈负相关; 同样, HFRS的发生与上一年的国内生产总值(GDP)也存在显著非线性效应(F_1.70,9.02 = 2.917, P < 0.05), 两者间也呈负相关。结构方程模型通过直接和间接的影响途径证明了这种转移机制, 发现温度对HFRS发生有显著的直接负向影响以及通过褐家鼠的间接正向影响; GDP对HFRS发生有直接的负向影响。本研究表明HFRS的发生与气候变化和经济发展相关, 两者均能影响HFRS的暴发, 该结论有助于今后更好地对HFRS疾病进行预防和控制。     

气候因素对黑线姬鼠种群动态影响的非线性效应

受全球气候变化的影响,气候因素与害鼠种群变化之间的关系成为害鼠防治研究中的热点问题。以西安市长安区周边分布的黑线姬鼠为研究对象,通过标志重捕法进行种群动态监测,掌握其种群数量的动态变化规律,并结合非线性的统计方法广义可加模型,对该地区2015—2018年黑线姬鼠种群密度和气候因素数据进行分析,探讨该鼠种群变化与气候因素之间的关系。结果表明,该地区黑线姬鼠种群数量总体显现为下降趋势。黑线姬鼠种群密度存在显著的正向自我调节效应(F_(1.00, 5.77)=27.062,P0.01),且与上一月种群密度存在线性的正相关。当月平均温度与该鼠种群密度之间存在显著的非线性效应(F_(1.90, 5.77 )=4.696,P0.05),两者之间显现为钟型关系,当温度21℃时,两者之间显现为正相关,黑线姬鼠种群密度随温度的升高而升高,反之显现为负相关。当月累计降雨量与其种群密度之间也存在显著的非线性效应(F_(1.87, 5.77)=3.879,P0.05),同样,两者之间也显现为钟型关系,当降雨量90 mm时,两者之间显现为负相关,种群密度随降雨量的增加而降低,反之显现为正相关。因此,温度和降雨对黑线姬鼠种群变化具有调节作用,低温干旱和高温多雨均不适合该鼠的繁殖与生长。     

国产西罗莫司与原研品在体内外对细胞影响的比较实验

目的探讨国产西罗莫司与原研品对移植宿主外周血中免疫细胞的影响效果。方法体外实验:人膀胱癌T24细胞体外培养,分别加入国产西罗莫司和原研品,CKK-8法检测并比较细胞增殖活性受抑制的情况。体内实验:建立小鼠异位心脏移植模型,设立对照无手术组(对照组)、移植无治疗组(Tx组)、移植+国产西罗莫司组(Tx+YXK组)、移植+原研品组(Tx+RAPA组)。观察移植心脏搏动情况,受者脾脏的流式细胞学检测,以及脾脏及移植物中免疫细胞浸润的病理检查。流式细胞检测树突状细胞(DC),CD8+细胞和调节性T细胞(Treg),病理组织学检测及免疫组化染色比较两组免疫细胞浸润情况。两组间比较采用独立样本t检验,多组间比较采用单因素方差分析,两两比较采用LSD-t检验。结果体外实验结果显示,国产西罗莫司与原研品对T24细胞活力影响的差异无统计学意义(P>0.05)。体内实验结果显示,Tx组移植心脏于第7天停止搏动,Tx+YXK组和Tx+RAPA组在第10天心脏搏动仍有力、节律正常。(1)脾脏流式细胞检测显示,与对照组、Tx组比较,Tx+RAPA组、Tx+YXK组CD11c+I-A+CD86+DC细胞(15.88±4.73、22.90±3.86比4.51±1.57、5.40±2.54)、CD8+淋巴细胞数量(6.32±0.98、6.75±1.34比3.03±1.12、3.23±0.97)均降低,而Tx+RAPA组CD4+CD25+Foxp3+阳性细胞数量(15.06±3.42比7.87±1.95,10.88±2.08)升高(P均<0.05)。Tx+YXK组和Tx+RAPA组3种免疫细胞数量差异均无统计学意义(P>0.05)。(2)移植心脏病理免疫细胞组化染色灰度分析,Tx组、Tx+YXK组和Tx+RAPA组CD4,CD8,IDO和CD11b数量差异无统计学意义(P>0.05),与Tx组比较,Tx+RAPA组和Tx+YXK组CD11c(25143.52±3525.12比12936.30±766.94、14240.60±3124.67)、Foxp3阳性细胞浸润数量(500.78±238.33比46.05±68.16、49.22±25.82)降低(P均<0.05),Tx+YXK组和Tx+RAPA组比较差异无统计学意义(P>0.05)。(3)模型动物脾脏病理免疫细胞组化染色灰度分析,Tx组CD 4和CD8阳性细胞浸润数量较Tx+YXK组和Tx+RAPA组少,但差异无统计学意义(P>0.05),Tx+YXK组和Tx+RAPA组比较,各种细胞染色的IOD值差异均无统计学意义。结论使用国产西罗莫司与原研品两种药物后受者移植心脏和脾脏中的细胞浸润变化一致;在体外对细胞增殖、移植后抗排斥作用和体内免疫细胞的影响表现均一致。     

Dexamethasone does not ameliorate gliosis in a mouse model of neurodegenerative disease

Prolonged neuroinflammation is a driving force for neurodegenerative disease, and agents against inflammatory responses are regarded as potential treatment strategies. Here we aimed to evaluate the prevention effects on gliosis by dexamethasone (DEX), an anti-inflammation drug. We used DEX to treat the nicastrin conditional knockout (cKO) mouse, a neurodegenerative mouse model. DEX (10 mg/kg) was given to 2.5-month-old nicastrin cKO mice, which have not started to display neurodegeneration and gliosis, for 2 months. Immunohistochemistry (IHC) and Western blotting techniques were used to detect changes in neuroinflammatory responses. We found that activation of glial fibrillary acidic protein (GFAP) positive or ionized calcium binding adapter molecule1 (Iba1) positive cells was not inhibited in nicastrin cKO mice treated with DEX as compared to those treated with saline. These data suggest that DEX does not prevent or ameliorate gliosis in a neurodegenerative mouse model when given prior to neuronal or synaptic loss.     

Straightforward method for calibration of mechanistic cation exchange chromatography models for industrial applications

Mechanistic modeling of chromatography processes is one of the most promising techniques for the digitalization of biopharmaceutical process development. Possible applications of chromatography models range from in silico process optimization in early phase development to in silico root cause investigation during manufacturing. Nonetheless, the cumbersome and complex model calibration still decelerates the implementation of mechanistic modeling in industry. Therefore, the industry demands model calibration strategies that ensure adequate model certainty in a limited amount of time. This study introduces a directed and straightforward approach for the calibration of pH-dependent, multicomponent steric mass action (SMA) isotherm models for industrial applications. In the case investigated, the method was applied to a monoclonal antibody (mAb) polishing step including four protein species. The developed strategy combined well-established theories of preparative chromatography (e.g. Yamamoto method) and allowed a systematic reduction of unknown model parameters to 7 from initially 32. Model uncertainty was reduced by designing two representative calibration experiments for the inverse estimation of remaining model parameters. Dedicated experiments with aggregate-enriched load material led to a significant reduction of model uncertainty for the estimates of this low-concentrated product-related impurity. The model was validated beyond the operating ranges of the final unit operation, enabling its application to late-stage downstream process development. With the proposed model calibration strategy, a systematic experimental design is provided, calibration effort is strongly reduced, and local minima are avoided.     

Down-regulation of miR-let-7e attenuates LPS-induced acute lung injury in mice via inhibiting pulmonary inflammation by targeting SCOS1/NF-κB pathway

Excessive pulmonary inflammatory response is critical in the development of acute lung injury (ALI). Previously, microRNAs (miRNAs) have been recognized as an important regulator of inflammation in various diseases. However, the effects and mechanisms of miRNAs on inflammatory response in ALI remain unclear. Herein, we tried to screen miRNAs in the processes of ALI and elucidate the potential mechanism. Using a microarray assay, microRNA let-7e (let-7e) was chose as our target for its reported suppressive roles in several inflammatory diseases. Down-regulation of let-7e by antagomiR-let-7e injection attenuated LPS-induced acute lung injury. We also found that antagomiR-let-7e could obviously improve the survival rate in ALI mice. Moreover, antagomiR-let-7e treatment reduced the production of proinflammatory cytokines (i.e., TNF-α, IL-1β and IL-6) in bronchoalveolar lavage fluid (BALF) of LPS-induced ALI mice. Luciferase reporter assays confirmed that suppressor of cytokine signaling 1 (SOCS1), a powerful attenuator of nuclear factor kappa B (NF-κB) signaling pathway, was directly targeted and suppressed by let-7e in RAW264.7 cells. In addition, it was further observed that SOCS1 was down-regulated, and inversely correlated with let-7e expression levels in lung tissues of ALI mice. Finally, down-regulation of let-7e suppressed the activation of NF-κB pathway, as evidenced by the reduction of p-IκBα, and nuclear p-p65 expressions in ALI mice. Collectively, our findings indicate that let-7e antagomir protects mice against LPS-induced lung injury via repressing the pulmonary inflammation though regulation of SOCS1/NF-κB pathway, and let-7e may act as a potential therapeutic target for ALI.     

Independent component analysis based gene co-expression network inference (ICAnet) to decipher functional modules for better single-cell clustering and batch integration

With the tremendous increase of publicly available single-cell RNA-sequencing (scRNA-seq) datasets, bioinformatics methods based on gene co-expression network are becoming efficient tools for analyzing scRNA-seq data, improving cell type prediction accuracy and in turn facilitating biological discovery. However, the current methods are mainly based on overall co-expression correlation and overlook co-expression that exists in only a subset of cells, thus fail to discover certain rare cell types and sensitive to batch effect. Here, we developed independent component analysis-based gene co-expression network inference (ICAnet) that decomposed scRNA-seq data into a series of independent gene expression components and inferred co-expression modules, which improved cell clustering and rare cell-type discovery. ICAnet showed efficient performance for cell clustering and batch integration using scRNA-seq datasets spanning multiple cells/tissues/donors/library types. It works stably on datasets produced by different library construction strategies and with different sequencing depths and cell numbers. We demonstrated the capability of ICAnet to discover rare cell types in multiple independent scRNA-seq datasets from different sources. Importantly, the identified modules activated in acute myeloid leukemia scRNA-seq datasets have the potential to serve as new diagnostic markers. Thus, ICAnet is a competitive tool for cell clustering and biological interpretations of single-cell RNA-seq data analysis.