Prediction of Antibiotic Resistance Evolution by Growth Measurement of All Proximal Mutants of Beta-Lactamase

The antibiotic resistance crisis continues to threaten human health. Better predictions of the evolution of antibiotic resistance genes could contribute to the design of more sustainable treatment strategies. However, comprehensive prediction of antibiotic resistance gene evolution via laboratory approaches remains challenging. By combining site-specific integration and high-throughput sequencing, we quantified relative growth under the respective selection of cefotaxime or ceftazidime selection in ∼23,000 Escherichia coli MG1655 strains that each carried a unique, single-copy variant of the extended-spectrum β-lactamase gene bla_CTX-M-14 at the chromosomal att HK022 site. Significant synergistic pleiotropy was observed within four subgenic regions, suggesting key regions for the evolution of resistance to both antibiotics. Moreover, we propose PEAR^P and PEAR^R, two deep-learning models with strong clinical correlations, for the prospective and retrospective prediction of bla_CTX-M-14 evolution, respectively. Single to quintuple mutations of bla_CTX-M-14 predicted to confer resistance by PEAR^P were significantly enriched among the clinical isolates harboring bla_CTX-M-14 variants, and the PEAR^R scores matched the minimal inhibitory concentrations obtained for the 31 intermediates in all hypothetical trajectories. Altogether, we conclude that the measurement of local fitness landscape enables prediction of the evolutionary trajectories of antibiotic resistance genes, which could be useful for a broad range of clinical applications, from resistance prediction to designing novel treatment strategies.     

Complexity and variability of gut commensal microbiota in polyphagous lepidopteran larvae

Background

The gut of most insects harbours nonpathogenic microorganisms. Recent work suggests that gut microbiota not only provide nutrients, but also involve in the development and maintenance of the host immune system. However, the complexity, dynamics and types of interactions between the insect hosts and their gut microbiota are far from being well understood.

Methods/Principal Findings

To determine the composition of the gut microbiota of two lepidopteran pests, Spodoptera littoralis and Helicoverpa armigera, we applied cultivation-independent techniques based on 16S rRNA gene sequencing and microarray. The two insect species were very similar regarding high abundant bacterial families. Different bacteria colonize different niches within the gut. A core community, consisting of Enterococci, Lactobacilli, Clostridia, etc. was revealed in the insect larvae. These bacteria are constantly present in the digestion tract at relatively high frequency despite that developmental stage and diet had a great impact on shaping the bacterial communities. Some low-abundant species might become dominant upon loading external disturbances; the core community, however, did not change significantly. Clearly the insect gut selects for particular bacterial phylotypes.

Conclusions

Because of their importance as agricultural pests, phytophagous Lepidopterans are widely used as experimental models in ecological and physiological studies. Our results demonstrated that a core microbial community exists in the insect gut, which may contribute to the host physiology. Host physiology and food, nevertheless, significantly influence some fringe bacterial species in the gut. The gut microbiota might also serve as a reservoir of microorganisms for ever-changing environments. Understanding these interactions might pave the way for developing novel pest control strategies.     

不经培养的农田土壤微生物种群构成及系统分类的初步研究

采用一系列的现代分子生物学技术,避开传统的分离培养过程,探讨自然界中微生物种群的基因多样性。经过直接从土壤中抽提总DNA,并对总DNA中16S rDNA V3可变区序列作PCR扩增、变性梯度凝胶电泳等,对农田土壤微生物种类分布进行初步的研究,发现不同的农田土壤间的菌种差异相当显著,同时对部分农田微生物的系统分类作了初步尝试,为农田土壤微生态和高效菌肥的研究提供了新的实验依据。     

2018年甘肃省平凉市流行性乙型脑炎病毒的分子特征

为研究甘肃省2018年蚊虫携带流行性乙型脑炎病毒(简称乙脑病毒)的分子特征,2018年7月上旬在甘肃省平凉市4个县采集蚊虫标本,采用实时荧光定量RT-PCR方法开展乙脑病毒筛查;通过高通量测序方法对乙脑病毒基因扩增阳性蚊虫标本进行深度测序研究.结果显示,本次调查在4个县共采集蚊虫1800只,均为三带喙库蚊,分36批研磨和检测.定量RT-PCR结果显示10批(27.8％)蚊虫样本呈乙脑病毒基因扩增阳性.对10批样本进行高通量测序共获得59.7 M读序,其中5.3 M(8.9％)条读序能够比对到病毒基因组数据库上,经注释属于14科15属28种病毒.在其中7批样本中检出乙脑序列共1357条,基因组覆盖度为9.5％-83.1％.系统进化分析显示甘肃省2018年采集的三带喙库蚊中乙脑病毒为基因Ⅰ型.     

A proteomic approach for plasma biomarker discovery with 8-plex iTRAQ labeling and SCX-LC-MS/MS

Plasma is recognized as a promising source of disease-related biomarkers, and proteomic approaches for identifying novel plasma biomarkers are in great demand. However, the complexity and dynamic protein concentration range of plasma remain the main obstacles for current research in this field. In this study, plasma proteins were prefractioned by immunodepletion and Protein Equalizer Technology to remove high abundant proteins, then labeled with an 8-plex isobaric tags for relative and absolute quantitation (iTRAQ) to improve the peptide ionization, and analyzed by strong-cation-exchange(SCX) coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Our results showed that both prefraction methods were complementary, with regard to the number of identified proteins. Good chromatographic technique is important to further fractionate the iTRAQ labeling peptides, which allowed 320 and 248 different proteins to be characterized from two prefraction methods, respectively, encompassing a wide array of biological functions and a broad dynamic range of 10⁷. Furthermore, the accuracy of iTRAQ relative quantitation for differentially expressed proteins is associated with the number of peptides hits per protein.