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《Analytical Chemistry》 | HOOKE单细胞分选仪助力耐药基因水平基因转移研究

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发布时间：2021-08-25

来源：酯香香化学采购网

　　【化工仪器网科技前沿】10月28日，中科院城市环境研究所崔丽研究员团队应用辰英核心产品——单细胞分选仪HOOKE PRECI SCS，在期刊《Analytical Chemistry》上发表文章“Phenotypic Tracking of Antibiotic Resistance Spread via Transformation from Environment to Clinic by Reverse D2O Single-Cell Raman Probing”。

　　01 研究背景

　　微生物耐药是一个危害公共卫生安全的性问题。耐药基因(antibiotic resistance gene，ARG)在环境或临床中出现并传播扩散。在这一过程中，水平基因转移(Horizontal gene transfer，HGT)现象起着不可忽视的作用。HGT的一个主要途径是转化(transformation)——受体细菌摄取胞外DNA(extracelluar DNA，eDNA)。这些eDNA多是细菌主动分泌或者裂解过程中释放的质粒DNA以及片段化DNA，常常携带着ARG。环境充当着ARG储库的角色，威胁着临床治疗。因此了解ARG从环境到临床转移的过程是必要的。

　　在上述问题的研究中，常规方法依赖耐药菌的选择性培养或是报告基因标记eDNA技术。前者需要已知被筛选微生物的培养条件，且无法筛选出耐药但扩增不活跃的微生物。后者需要对eDNA等进行改造，不能反应实际的HGT情况。

　　近年新兴了一种联合正向D2O标记的单细胞拉曼光谱方法用于微生物抗性区分。微生物利用环境中的D2O合成相关的生物分子，可以通过拉曼光谱的C-D带(2040-2300 cm-1)进行表征。抗性环境中敏感菌与耐药菌会表现出不同D2O摄入，进而表现出不同的C-D峰情况。然而微生物不仅摄入D2O，还会摄入其他含H元素的营养物质，这导致单位时间C-D谱带的增长较低。同时较短时间的孵育也降低了该方法的灵敏度。作者团队改进并提出了反向D2O-单细胞-拉曼检测技术(reverse D2O single-cell Raman (Raman-rD2O) probing，Raman-rD2O)。微生物预先在D2O中孵育，后置换为含抗生素的H2O环境孵育并被检测。作者确定了该方法的有效性并利用该方法研究了HGT过程.。

　　02 实验设计

　　这项研究中，为了评价微生物耐药性，作者建立了Raman-rD2O方法，确定了其有效性，以及灵敏度。之后在大肠杆菌体系中确认了水平基因转移的情况。接着评价了与来自于复杂环境中质粒共孵育的大肠杆菌对各抗生素(meropenem，vancomycin，ampicillin，cefradine以及ciprofloxacin)的耐药情况，并确认了该方法比传统培养方法更加准确。后提出了一种用于反映ARGs传播风险的计算方法。

　　03 结果讨论

　　Raman-rD2O方法区分耐药菌以及敏感菌的灵敏度

　　对colistin耐药的FIT10(B. cereus)以及colistin敏感的DH5α(E. coli)菌株进行D2O培养12h。转移至含抗生素colistin的无D2O环境进行培养，取不同时间点进行拉曼图谱采集，结果如图 1。在C-D峰处可以看出，耐药菌FIT10峰强逐渐变低，非耐药菌DH5α无明显变化。

　　图 1. 预先标记同位素D微生物在含0.125 mg/L colistin的LB培养基中培养0、0.5、1、4、8小时后的单细胞拉曼光谱(a)耐药菌FIT10，(b)敏感菌DH5α。

　　采集含colistin培养条件下FIT10以及DH5α的单细胞拉曼图谱并统计C-D比值(CD/(CD + CH))，结果如图 2a-Ⅰ。另外比较了含ampicillin条件下的DH5α-Ampr以及DH5α数据，如图 2a-Ⅲ。可以看出该方法能够区分耐药菌以及敏感菌，且适用不同抗生素。

　　从图 2a-Ⅱ/Ⅲ以及2b数据，可以看出正向标记方法4h后才能观察到差异。因此反向标记方法是优于正向标记的。

　　图 2. (a-Ⅰ，a-Ⅲ) 反向D2O方法下，不同时间点的colistin耐药FIT10、ampicilin耐药DH5α-Ampr以及DH5α的C-D比值统计结果；(a-Ⅲ，a-Ⅳ) 正向D2O方法下结果；(b) 1×MIC抗生素浓度下培养1h，反向D2O、正向D2O的单细胞拉曼图谱C-D区域结果。

　　利用Raman-rD2O方法揭示转化过程中ARGs的水平基因转移

　　作者比较了实验组JM109(E . coli)以及对照组DH5α、DH5α-Ampr 菌C-D比值。JM109预先与携带bla基因(编码抗ampicilin蛋白)的pMD19-T质粒共孵育。从图 3可以看出，DH5α组维持高的C-D比值，DH5α-Ampr 组比值降至6.4%以下。而JM109组分为了高比值群体以及低比值群体。这意味着JM109组中部分微生物获得了bla基因并表达，从而能在含ampicilin环境中进行代谢生长。

　　为了验证这一假设，作者利用本公司(HOOKE instruments)产品单细胞分选仪(PRECI SCS)，对各样品进行了单个细胞分选。对分选的单个微生物进行全基因组扩增后，通过PCR验证bla基因的携带情况。从图 3b可看出，DH5α组无bla基因，DH5α-Ampr 组携带bla基因，部分JM109组携带bla基因。这一结果印证了bla基因转移的假设。

　　作者统计了不同采集个数下耐药菌个数并计算了转化频率(Transformation Frequency = 转化菌个数/(10×拉曼采集总数)，10为微生物1h时扩增倍数)。采集数目大于40时，转化频率趋近4.33 × 10-2。该结果与传统平板培养方法得到的5.07 × 10-2一致。

　　图 3. (a)预标记同位素D的E. coli DH5α(敏感对照)，E. coli DH5α-Ampr(抵抗对照)以及转化了含bla基因质粒的接受菌E. coli ，经过含ampicillin的LB培养基孵育1h，采集拉曼光谱并统计C-D比率。每个点对应一个拉曼结果。阈值6.4%为未经过D标记的抗性转化子的C-D比值的平均值+3倍标准偏差；(b)PCR产物(针对质粒上bla基因)的电泳结果，1-3道为高C-D比值的敏感接受菌，4-6为小于10% C-D比值的耐药接受菌，7为不含质粒的E. coli DH5α，8为含bla基因的E. coli DH5α-Ampr；(c)质粒(携带bla基因)的转化频率(线)以及转化频率的标准偏差(柱)。利用单细胞Raman-rD2O方法对不同拉曼图谱采集个数下结果进行了统计。

　　通过单细胞Raman-rD2O评价复杂环境中质粒介导的eARGs转化现象

　　作者提取了土壤中的质粒并与E. coli共孵育。通过单细胞Raman-D2O，分析了不同抗生素下(meropenem，vancomycin，ampicillin，cefradine以及ciprofloxacin)的拉曼C-D比值。从图 4a可以看出，ampicillin，cefradine以及ciprofloxacin组出现了水平基因转移现象。考虑到土壤等环境中质粒对受体微生物增殖能力的影响，不同质粒编码导致同一抗性等问题，作者引入了传播效率(Spread Efficiency = 转化菌个数/拉曼采集总数)来评估传播风险。就图 4b结果来说，传播效率ampicillin(1.5 × 10-1) > cefradine(8.6 × 10-2)和ciprofloxacin(6.7 × 10-2) >meropene(0)m和 vancomycin(0)。

　　作者同时计算了Raman rD2O方法的转化效率，ampicillin (1.9 × 10-3)> ciprofloxacin (5.9 × 10-4) and cefradine (8.8 × 10-4) >meropenem and vancomycin (0) 。而传统平皿培养方法下的转化效率数值小于上述80-100倍。传统方法低估了HGT的程度，一方面存在携带抗性基因但在环境下不可培养鉴定的微生物(viable but nonculturable，VBNC)，另一方面存在接受质粒导致扩增速率大幅降低(1000倍)的微生物。而在传统方法中过夜培养后，这种差异变得更加的明显。

　　图 4. (a) E. coli DH5α(敏感对照)C-D比值，以及接受菌E. coli 的C-D比值。接受菌经同位素D预标记后，与从土壤提取质粒进行共孵育。后分别在meropenem，vancomycin，ampicillin，cefradine以及ciprofloxacin条件下孵育1h。每一个点对应一个单细胞拉曼图谱。C-D比值小于6.4%的为不带D标记的耐受转化子；(b)携带抗meropenem，vancomycin，ampicillin，cefradine以及ciprofloxacin基因的质粒的传播效率。星号表示比较具有统计学意义(单因素方差分析ANOVA，P< 0.001)。

　　04 结论

　　利用单细胞拉曼反向D2O检测方法能够可靠且快速的从表型上追踪耐药从环境到临床的扩散。方法具有很高的灵敏度，能够在大量受体菌种识别出那些少量的抗性转化子。单细胞水平的检测避免了繁琐的培养过程，可以直接计算传播效率，能够表征临床相关抗生素的不同风险。该方法后续未来可用于破解影响抗性质粒转移以及持续的因素。通过与基因型研究的联系，能更好的理解环境质体(environmental plastidome)传播风险。也是一种研究HGT机制的新手段。

　　辰英科仪自主研制的单细胞分选仪PRECI SCS具有独特的可视化分选功能，所见即所得，精准实现目标细胞的逐一分离。采用独特的激光与物质相互作用原理，对于复杂生物样本中形态各异的细胞，可实现非标记状态下的精准分离。对于百纳米级的单个微生物细胞也同样适用。

　　图5. 单细胞分选仪HOOKE PRECI SCS

　　图6. 拉曼单细胞分选仪HOOKE PRECI SCS-R300

　　PRECI SCS具有可视化、广泛适用等特点。分选过程不依赖标记，可与形态、拉曼、荧光等多种识别方式结合，多种机型可选，满足不同应用需求。搭载潜心研制的HOOKE IntP智能软件，实现单细胞图像智能识别、一键自动分选、全自动细胞获取等。设备操作流程简易，为单细胞测序、未培养微生物开发、工程细胞筛选、细胞图谱绘制等研究提供解决方案，助力前沿科学研究。

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[ DB ] CONNECT:[ UseTime:0.000297s ] mysql:host=127.0.0.1;port=3306;dbname=yzncms;charset=utf8
[ SQL ] SHOW COLUMNS FROM `yzn_poster` [ RunTime:0.000851s ]
[ SQL ] SELECT * FROM `yzn_poster` WHERE `cate_id` = 99 AND `p_c_id` = 52 AND `status` = 1 LIMIT 1 [ RunTime:0.000381s ]
[ SQL ] SELECT * FROM `yzn_poster` WHERE `cate_id` = 99 AND `p_c_id` = 55 AND `status` = 1 LIMIT 1 [ RunTime:0.000267s ]
[ SQL ] SHOW COLUMNS FROM `yzn_goods_property` [ RunTime:0.000740s ]
[ SQL ] SELECT `g`.`name`,`p`.`price`,`p`.`unit`,`p`.`type`,`p`.`thumb`,p.id as p_id,`p`.`value`,`p`.`is_where`,`p`.`sku_unit`,`p`.`repeat_type`,`p`.`goods_id` FROM `yzn_goods_property` `p` LEFT JOIN `yzn_goods` `g` ON `p`.`goods_id`=`g`.`id` WHERE `p`.`status` = 1 AND `p`.`is_del` = 0 AND `g`.`is_del` = 0 AND `p`.`is_where` LIKE '%1%' AND `p`.`recommend` = 1 GROUP BY `p`.`goods_id`,`p`.`repeat_type` ORDER BY `p`.`sort` DESC,`g`.`id` DESC LIMIT 0,15 [ RunTime:0.002272s ]
[ SQL ] SHOW COLUMNS FROM `yzn_goods_category` [ RunTime:0.000652s ]
[ SQL ] SELECT * FROM `yzn_goods_category` WHERE `hot_search` = 1 AND `status` = 1 ORDER BY `listorder` ASC,`id` DESC [ RunTime:0.000427s ]
[ SQL ] SELECT * FROM `yzn_goods_category` WHERE `is_show` > 0 AND `status` = 1 ORDER BY `listorder` ASC [ RunTime:0.000324s ]
[ SQL ] SELECT * FROM `yzn_goods_category` WHERE `id` IN (1,2,7,16,17,34,92,95,38) [ RunTime:0.000263s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 1 AND `status` = 1 ORDER BY `listorder` ASC,`id` DESC [ RunTime:0.000247s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 2 AND `status` = 1 ORDER BY `listorder` ASC,`id` DESC [ RunTime:0.000230s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 7 AND `status` = 1 ORDER BY `listorder` ASC,`id` DESC [ RunTime:0.000216s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 16 AND `status` = 1 ORDER BY `listorder` ASC,`id` DESC [ RunTime:0.000228s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 17 AND `status` = 1 ORDER BY `listorder` ASC,`id` DESC [ RunTime:0.000224s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` IN (34,92) AND `status` = 1 ORDER BY `listorder` ASC,`id` DESC [ RunTime:0.000216s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` IN (95,38) AND `status` = 1 ORDER BY `listorder` ASC,`id` DESC [ RunTime:0.000250s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 1 AND `status` = 1 [ RunTime:0.000202s ]
[ SQL ] SELECT * FROM `yzn_goods_category` WHERE `status` = 1 AND `id` = 1 [ RunTime:0.000199s ]
[ SQL ] SELECT `id` FROM `yzn_goods_category` WHERE `status` = 1 AND ( arrparentid like '0,1,%' ) [ RunTime:0.000233s ]
[ SQL ] SHOW COLUMNS FROM `yzn_goods` [ RunTime:0.000632s ]
[ SQL ] SELECT `g`.`name`,p.id as p_id,`p`.`price`,`p`.`type`,`p`.`thumb`,`p`.`unit`,`p`.`is_where`,`p`.`goods_id`,`p`.`repeat_type` FROM `yzn_goods` `g` LEFT JOIN `yzn_goods_property` `p` ON `p`.`goods_id`=`g`.`id` WHERE `p`.`status` = 1 AND `p`.`is_del` = 0 AND `g`.`is_del` = 0 AND `p`.`is_where` LIKE '%1%' AND `g`.`cate_id` IN (25,26,29,30,48,1) AND `p`.`hot_sale` = '1' GROUP BY `p`.`repeat_type`,`p`.`goods_id` ORDER BY `p`.`sort` DESC,`p`.`id` DESC LIMIT 0,10 [ RunTime:0.001007s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 2 AND `status` = 1 [ RunTime:0.000246s ]
[ SQL ] SELECT * FROM `yzn_goods_category` WHERE `status` = 1 AND `id` = 2 [ RunTime:0.000216s ]
[ SQL ] SELECT `id` FROM `yzn_goods_category` WHERE `status` = 1 AND ( arrparentid like '0,2,%' ) [ RunTime:0.000196s ]
[ SQL ] SELECT `g`.`name`,p.id as p_id,`p`.`price`,`p`.`type`,`p`.`thumb`,`p`.`unit`,`p`.`is_where`,`p`.`goods_id`,`p`.`repeat_type` FROM `yzn_goods` `g` LEFT JOIN `yzn_goods_property` `p` ON `p`.`goods_id`=`g`.`id` WHERE `p`.`status` = 1 AND `p`.`is_del` = 0 AND `g`.`is_del` = 0 AND `p`.`is_where` LIKE '%1%' AND `g`.`cate_id` IN (42,43,2) AND `p`.`hot_sale` = '1' GROUP BY `p`.`repeat_type`,`p`.`goods_id` ORDER BY `p`.`sort` DESC,`p`.`id` DESC LIMIT 0,10 [ RunTime:0.000938s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 7 AND `status` = 1 [ RunTime:0.000214s ]
[ SQL ] SELECT * FROM `yzn_goods_category` WHERE `status` = 1 AND `id` = 7 [ RunTime:0.000200s ]
[ SQL ] SELECT `id` FROM `yzn_goods_category` WHERE `status` = 1 AND ( arrparentid like '0,7,%' ) [ RunTime:0.000196s ]
[ SQL ] SELECT `g`.`name`,p.id as p_id,`p`.`price`,`p`.`type`,`p`.`thumb`,`p`.`unit`,`p`.`is_where`,`p`.`goods_id`,`p`.`repeat_type` FROM `yzn_goods` `g` LEFT JOIN `yzn_goods_property` `p` ON `p`.`goods_id`=`g`.`id` WHERE `p`.`status` = 1 AND `p`.`is_del` = 0 AND `g`.`is_del` = 0 AND `p`.`is_where` LIKE '%1%' AND `g`.`cate_id` IN (10,14,32,33,49,50,51,52,53,54,55,56,57,58,96,97,7) AND `p`.`hot_sale` = '1' GROUP BY `p`.`repeat_type`,`p`.`goods_id` ORDER BY `p`.`sort` DESC,`p`.`id` DESC LIMIT 0,10 [ RunTime:0.000966s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 16 AND `status` = 1 [ RunTime:0.000226s ]
[ SQL ] SELECT * FROM `yzn_goods_category` WHERE `status` = 1 AND `id` = 16 [ RunTime:0.000200s ]
[ SQL ] SELECT `id` FROM `yzn_goods_category` WHERE `status` = 1 AND ( arrparentid like '0,16,%' ) [ RunTime:0.000213s ]
[ SQL ] SELECT `g`.`name`,p.id as p_id,`p`.`price`,`p`.`type`,`p`.`thumb`,`p`.`unit`,`p`.`is_where`,`p`.`goods_id`,`p`.`repeat_type` FROM `yzn_goods` `g` LEFT JOIN `yzn_goods_property` `p` ON `p`.`goods_id`=`g`.`id` WHERE `p`.`status` = 1 AND `p`.`is_del` = 0 AND `g`.`is_del` = 0 AND `p`.`is_where` LIKE '%1%' AND `g`.`cate_id` IN (59,60,61,62,63,16) AND `p`.`hot_sale` = '1' GROUP BY `p`.`repeat_type`,`p`.`goods_id` ORDER BY `p`.`sort` DESC,`p`.`id` DESC LIMIT 0,10 [ RunTime:0.000924s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 17 AND `status` = 1 [ RunTime:0.000229s ]
[ SQL ] SELECT * FROM `yzn_goods_category` WHERE `status` = 1 AND `id` = 17 [ RunTime:0.000205s ]
[ SQL ] SELECT `id` FROM `yzn_goods_category` WHERE `status` = 1 AND ( arrparentid like '0,17,%' ) [ RunTime:0.000219s ]
[ SQL ] SELECT `g`.`name`,p.id as p_id,`p`.`price`,`p`.`type`,`p`.`thumb`,`p`.`unit`,`p`.`is_where`,`p`.`goods_id`,`p`.`repeat_type` FROM `yzn_goods` `g` LEFT JOIN `yzn_goods_property` `p` ON `p`.`goods_id`=`g`.`id` WHERE `p`.`status` = 1 AND `p`.`is_del` = 0 AND `g`.`is_del` = 0 AND `p`.`is_where` LIKE '%1%' AND `g`.`cate_id` IN (40,64,65,66,67,68,100,17) AND `p`.`hot_sale` = '1' GROUP BY `p`.`repeat_type`,`p`.`goods_id` ORDER BY `p`.`sort` DESC,`p`.`id` DESC LIMIT 0,10 [ RunTime:0.000927s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 34 AND `status` = 1 [ RunTime:0.000222s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 92 AND `status` = 1 [ RunTime:0.000197s ]
[ SQL ] SELECT * FROM `yzn_goods_category` WHERE `status` = 1 AND `id` IN (34,92) [ RunTime:0.000248s ]
[ SQL ] SELECT `id` FROM `yzn_goods_category` WHERE `status` = 1 AND ( arrparentid like '0,34,%' or arrparentid like '0,92,%' ) [ RunTime:0.000215s ]
[ SQL ] SELECT `g`.`name`,p.id as p_id,`p`.`price`,`p`.`type`,`p`.`thumb`,`p`.`unit`,`p`.`is_where`,`p`.`goods_id`,`p`.`repeat_type` FROM `yzn_goods` `g` LEFT JOIN `yzn_goods_property` `p` ON `p`.`goods_id`=`g`.`id` WHERE `p`.`status` = 1 AND `p`.`is_del` = 0 AND `g`.`is_del` = 0 AND `p`.`is_where` LIKE '%1%' AND `g`.`cate_id` IN (35,70,71,93,94,34,92) AND `p`.`hot_sale` = '1' GROUP BY `p`.`repeat_type`,`p`.`goods_id` ORDER BY `p`.`sort` DESC,`p`.`id` DESC LIMIT 0,10 [ RunTime:0.000954s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 95 AND `status` = 1 [ RunTime:0.000246s ]
[ SQL ] SELECT `id`,`catname` FROM `yzn_goods_category` WHERE `pid` = 38 AND `status` = 1 [ RunTime:0.000220s ]
[ SQL ] SELECT * FROM `yzn_goods_category` WHERE `status` = 1 AND `id` IN (95,38) [ RunTime:0.000259s ]
[ SQL ] SELECT `id` FROM `yzn_goods_category` WHERE `status` = 1 AND ( arrparentid like '0,38,%' or arrparentid like '0,95,%' ) [ RunTime:0.000244s ]
[ SQL ] SELECT `g`.`name`,p.id as p_id,`p`.`price`,`p`.`type`,`p`.`thumb`,`p`.`unit`,`p`.`is_where`,`p`.`goods_id`,`p`.`repeat_type` FROM `yzn_goods` `g` LEFT JOIN `yzn_goods_property` `p` ON `p`.`goods_id`=`g`.`id` WHERE `p`.`status` = 1 AND `p`.`is_del` = 0 AND `g`.`is_del` = 0 AND `p`.`is_where` LIKE '%1%' AND `g`.`cate_id` IN (47,74,75,76,77,78,79,80,81,82,83,99,95,38) AND `p`.`hot_sale` = '1' GROUP BY `p`.`repeat_type`,`p`.`goods_id` ORDER BY `p`.`sort` DESC,`p`.`id` DESC LIMIT 0,10 [ RunTime:0.000941s ]
[ SQL ] SHOW COLUMNS FROM `yzn_article` [ RunTime:0.000639s ]
[ SQL ] SELECT `A`.*,`AD`.*,`C`.`catname` FROM `yzn_article` `A` INNER JOIN `yzn_article_data` `AD` ON `A`.`id`=`AD`.`did` INNER JOIN `yzn_category` `C` ON `C`.`id`=`A`.`catid` WHERE `A`.`id` = 5630 AND `A`.`status` = 1 LIMIT 1 [ RunTime:0.000473s ]
[ SQL ] SHOW COLUMNS FROM `yzn_category` [ RunTime:0.000632s ]
[ SQL ] SELECT `id` FROM `yzn_category` WHERE `parentid` = 35 AND `status` = 1 [ RunTime:0.000207s ]
[ SQL ] SELECT `id` FROM `yzn_category` WHERE `parentid` IN (36,37,38,39,40,41,42) AND `status` = 1 [ RunTime:0.000227s ]
[ SQL ] SELECT `id` FROM `yzn_category` WHERE `parentid` = 43 AND `status` = 1 [ RunTime:0.000203s ]
[ SQL ] SELECT `id` FROM `yzn_category` WHERE `parentid` IN (44,45,46,47,48,49,50) AND `status` = 1 [ RunTime:0.000190s ]
[ SQL ] SELECT `id` FROM `yzn_category` WHERE `parentid` = 6 AND `status` = 1 [ RunTime:0.000192s ]
[ DB ] CONNECT:[ UseTime:0.000236s ] mysql:host=127.0.0.1;port=3306;dbname=yzncms;charset=utf8
[ SQL ] SELECT `A`.`id`,`A`.`title` FROM `yzn_article` `A` INNER JOIN `yzn_category` `C` ON `C`.`id`=`A`.`catid` WHERE `A`.`status` = 1 AND `A`.`catid` IN (35,36,37,38,39,40,41,42) ORDER BY `A`.`flag` DESC,`A`.`listorder` ASC,`A`.`updatetime` DESC [ RunTime:0.020455s ]
[ SQL ] UPDATE `yzn_article` SET `hits` = `hits` + 1 WHERE `id` = 5630 [ RunTime:0.000283s ]
[ SQL ] SELECT * FROM `yzn_poster` WHERE `cate_id` = 10 AND `p_c_id` = 41 ORDER BY `listorder` ASC LIMIT 4 [ RunTime:0.000330s ]
[ SQL ] SELECT COUNT(*) AS tp_count FROM `yzn_article` `a` INNER JOIN `yzn_category` `c` ON `a`.`catid`=`c`.`id` WHERE `catid` = 38 AND `a`.`status` = 1 [ RunTime:0.002590s ]
[ SQL ] SELECT `a`.*,`c`.`catname` FROM `yzn_article` `a` INNER JOIN `yzn_category` `c` ON `a`.`catid`=`c`.`id` WHERE `catid` = 38 AND `a`.`status` = 1 ORDER BY `flag` DESC,`listorder` ASC,`updatetime` DESC LIMIT 0,6 [ RunTime:0.004701s ]
[ SQL ] SELECT COUNT(*) AS tp_count FROM `yzn_article` `a` INNER JOIN `yzn_category` `c` ON `a`.`catid`=`c`.`id` WHERE `catid` = 37 AND `a`.`status` = 1 [ RunTime:0.002513s ]
[ SQL ] SELECT `a`.*,`c`.`catname` FROM `yzn_article` `a` INNER JOIN `yzn_category` `c` ON `a`.`catid`=`c`.`id` WHERE `catid` = 37 AND `a`.`status` = 1 ORDER BY `flag` DESC,`listorder` ASC,`updatetime` DESC LIMIT 0,6 [ RunTime:0.004898s ]