分娩方式对婴儿出生后一年内肠道菌群的影响

目的探讨不同分娩方式对婴儿出生后1年内肠道菌群定植的影响。方法选取45例新生儿为研究对象,根据分娩方式分为自然分娩组(n=27)和剖宫产组(n=18)。收集婴儿出生后0(胎粪)、3、6和12个月的粪便标本,应用高通量测序技术分析肠道菌群多样性及组成。结果与自然分娩组比较,在0个月时剖宫产组婴儿粪便标本拟杆菌门的相对丰度显著降低(Z=-2.374 1,P=0.017 6)。2组研究对象中,除自然分娩组和剖宫产组0个月时婴儿粪便标本分别以埃希菌-志贺菌属和克雷伯菌属为优势菌属外,余下均以双歧杆菌属为优势菌属。相比于自然分娩组,在0个月时剖宫产组婴儿粪便标本埃希菌-志贺菌属和肠杆菌属所占比例显著降低(Z=-2.136 4,P=0.032 7;Z=-2.940 8,P=0.003 3),克雷伯菌属和罗氏菌属所占比例显著升高(Z=-2.642 4,P=0.008 2;Z=-2.299 4,P=0.021 5);6个月时罗氏菌属所占比例显著降低(Z=-2.045 0,P=0.040 9),肠球菌属所占比例显著升高(Z=-2.109 2,P=0.034 9)。结论不同分娩方式下的婴儿肠道菌群的构成存在显著差异。     

补充益生菌对功能性腹泻患者焦虑抑郁状态的影响

目的探讨益生菌对功能性腹泻患者临床症状和心理健康的影响。方法将2019年3月至2019年12月在广东省肇庆市高要区人民医院消化内科门诊收治的伴有焦虑抑郁状态的90例功能性腹泻住院病人随机分为试验组、对照组A、对照组B。三组受试者均口服匹维溴铵,试验组口服双歧杆菌四联活菌,对照组A服用氟西汀,对照组B未给其他药物治疗,疗程均为1个月。治疗前后,比较患者大便次数及性状、汉密尔顿焦虑量表(HAMA)和汉密尔顿抑郁量表(HAMD)评分。结果治疗前三组患者每周排便不同次数的人数比较,差异无统计学意义(P0.05)。治疗第3周和第4周后,与对照组A相比,对照组B和试验组的排便不同次数的人数差异具有统计学意义(P0.05)。治疗第4周后,试验组与对照组B的排便不同次数的人数比较,差异具有统计学意义(P0.05)。治疗前3组患者Bristol粪便性状评分比较差异无统计学意义(P0.05)。治疗第3和第4周后,与对照组A相比,对照组B和试验组的Bristol粪便性状评分比较,差异有统计学意义(P0.05)。治疗第4周后,试验组与对照组B的Bristol粪便性状评分比较,差异有统计学意义(P0.05)。治疗后与对照组A比较,对照组B和试验组HAMA评分和HAMD评分显著低于对照组A,且差异具有统计学意义(P0.05)。与对照组B比较,试验组HAMA评分和HAMD评分显著低于对照组B(P0.05)。结论通过补充益生菌可调节功能性腹泻患者腹泻次数,提高功能性腹泻患者生活质量,改善患者焦虑抑郁症状。     

木耳‘农黑1号'的选育报告

黑木耳新品种‘农黑1号'是以黑木耳‘Au5'和‘木耳黑龙3号'作为亲本菌株,通过单孢杂交配对选育而来。工厂化条件下的生产性试验结果表明：‘农黑1号'的第一潮平均鲜耳产量达到322.4g/袋,干耳产量平均为29.0g/袋,出耳率平均为93.3%,生产周期平均为71d。综合来看,‘农黑1号'具有产量高、周期短、出耳率高、一致性好等优点,可作为黑木耳工厂化栽培的优良新品种。     

Crystal structure of Drosophila melanogaster tryptophan 2,3-dioxygenase reveals insights into substrate recognition and catalytic mechanism

Tryptophan 2,3-dioxygenase (TDO) catalyzes the oxidative cleavage of the indole ring of l-tryptophan to N-formylkynurenine in the kynurenine pathway, and is considered as a drug target for cancer immunotherapy. Here, we report the first crystal structure of a eukaryotic TDO from Drosophila melanogaster (DmTDO) in complex with heme at 2.7 Å resolution. DmTDO consists of an N-terminal segment, a large domain and a small domain, and assumes a tetrameric architecture. Compared with prokaryotic TDOs, DmTDO contains two major insertion sequences: one forms part of the heme-binding site and the other forms a large portion of the small domain. The small domain which is unique to eukaryotic TDOs, interacts with the active site of an adjacent monomer and plays a role in the catalysis. Molecular modeling and dynamics simulation of DmTDO-heme-Trp suggest that like prokaryotic TDOs, DmTDO adopts an induced-fit mechanism to bind l-Trp; in particular, two conserved but flexible loops undergo conformational changes, converting the active site from an open conformation to a closed conformation. The functional roles of the key residues involved in recognition and binding of the heme and the substrate are verified by mutagenesis and kinetic studies. In addition, a modeling study of DmTDO in complex with the competitive inhibitor LM10 provides useful information for further inhibitor design. These findings reveal insights into the substrate recognition and the catalysis of DmTDO and possibly other eukaryotic TDOs and shed lights on the development of effective anti-TDO inhibitors.     

A Fast Workflow for Identification and Quantification of Proteomes

The current in-depth proteomics makes use of long chromatography gradient to get access to more peptides for protein identification, resulting in covering of as many as 8000 mammalian gene products in 3 days of mass spectrometer running time. Here we report a fast sequencing (Fast-seq) workflow of the use of dual reverse phase high performance liquid chromatography - mass spectrometry (HPLC-MS) with a short gradient to achieve the same proteome coverage in 0.5 day. We adapted this workflow to a quantitative version (Fast quantification, Fast-quan) that was compatible to large-scale protein quantification. We subjected two identical samples to the Fast-quan workflow, which allowed us to systematically evaluate different parameters that impact the sensitivity and accuracy of the workflow. Using the statistics of significant test, we unraveled the existence of substantial falsely quantified differential proteins and estimated correlation of false quantification rate and parameters that are applied in label-free quantification. We optimized the setting of parameters that may substantially minimize the rate of falsely quantified differential proteins, and further applied them on a real biological process. With improved efficiency and throughput, we expect that the Fast-seq/Fast-quan workflow, allowing pair wise comparison of two proteomes in 1 day may make MS available to the masses and impact biomedical research in a positive way.The performance of mass spectrometry has been improved tremendously over the last few years (1–3), making mass spectrometry-based proteomics a viable approach for large-scale protein analysis in biological research. Scientists around the world are striving to fulfill the promise of identifying and quantifying almost all gene products expressed in a cell line or tissue. This would make mass spectrometry-based protein analysis an approach that is compatible to the second-generation mRNA deep-seq technique (4, 5).Two liquid chromatography (LC)-MS strategies have been employed to achieve deep proteome coverage. One is a single run with a long chromatography column and gradient to take advantage of the resolving power of HPLC to reduce the complexity of peptide mixtures; the other is a sequential run with two-dimensional separation (typically ion-exchange and reverse phase) to reduce peptide complexity. It was reported by two laboratories that 2761 and 4500 proteins were identified with a 10 h chromatography gradient on a dual pressure linear ion-trap orbitrap mass spectrometer (LTQ Orbitrap Velos)(6–8). Similarly, 3734 proteins were identified using a 8 h gradient on a 2 m long column with a hybrid triple quadrupole - time of flight (Q-TOF, AB sciex 5600 Q-TOF)(9) mass spectrometer. The two-dimensional approach has yielded more identification with longer time. For example, 10,006 proteins (representing over 9000 gene products, GPs)¹ were identified in U2OS cell (10), and 10,255 proteins (representing 9207 GPs) from HeLa cells (11). It took weeks (for example, 2–3 weeks) of machine running time to achieve such proteome coverage, pushing proteome analysis to the level that is comparable to mRNA-seq. With the introduction of faster machines, human proteome coverage now has reached the level of 7000–8500 proteins (representing 7000–8000 GPs) in 3 days (12). Notwithstanding the impressive improvement, the current approach using long column and long gradient suffers from inherent limitations: it takes long machine running time and it is challenging to keep reproducibility among repeated runs. Thus, current throughput and reproducibility have hindered the application of in-depth proteomics to traditional biological researches. A timesaving approach is in urgent need.In this study, we used the first-dimension (1D) short pH 10 RP prefractionation to reduce the complexity of the proteome (13), followed by sequential 30 min second-dimension (2D) short pH 3 reverse phase-(RP)-LC-MS/MS runs for protein identification (14). The results demonstrated that it is possible to identify 8000 gene products from mammalian cells within 12 h of total MS measurement time by applying this dual-short 2D-RPLC-MS/MS strategy (Fast sequencing, Fast-seq). The robustness of the strategy was revealed by parallel testing on different MS systems including quadrupole orbitrap mass spectrometer (Q-Exactive), hybrid Q-TOF (Triple-TOF 5600), and dual pressure linear ion-trap orbitrap mass spectrometer (LTQ-Orbitrap Velos), indicating the inherent strength of the approach as to merely taking advantage of the better MS instruments. This strategy increases the efficiency of MS sequencing in unit time for the identification of proteins. We achieved identification of 2200 proteins/30 mins on LTQ-Orbitrap Velos, 2800 proteins/30 mins on Q-Exactive and Triple-TOF 5600 respectively. We further optimized Fast-seq and worked out a quantitative-version of the Fast-seq workflow: Fast-quantification (Fast-quan) and applied it for protein abundance quantification in HUVEC cell that was treated with a drug candidate MLN4924 (a drug in phase III clinical trial). We were able to quantify > 6700 GPs in 1 day of MS running time and found 99 proteins were up-regulated with high confidence. We expect this efficient alternative approach for in-depth proteome analysis will make the application of MS-based proteomics more accessible to biological applications.     

Rational design of microRNA–siRNA chimeras for multifunctional target suppression

MicroRNAs (miRNAs) are involved in a variety of human diseases by simultaneously suppressing many gene targets. Thus, the therapeutic value of miRNAs has been intensely studied. However, there are potential limitations with miRNA-based therapeutics such as a relatively moderate impact on gene target regulation and cellular phenotypic control. To address these issues, we proposed to design new chimeric small RNAs (aiRNAs) by incorporating sequences from both miRNAs and siRNAs. These aiRNAs not only inherited functions from natural miRNAs, but also gained new functions of gene knockdown in an siRNA-like fashion. The improved efficacy of multifunctional aiRNAs was demonstrated in our study by design and testing of an aiRNA that inherited the functions of both miR-200a and an AKT1-targeting siRNA for simultaneous suppression of cancer cell motility and proliferation. The general principles of aiRNA design were further validated by engineering new aiRNAs mimicking another miRNA, miR-9. By regulating multiple cellular functions, aiRNAs could be used as an improved tool over miRNAs to target disease-related genes, thus alleviating our dependency on a limited number of miRNAs for the development of RNAi-based therapeutics.