Kang Ning

Chinese Academy of Medical Sciences & Peking Union Medical College

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Jian Xu

Qingdao Institute of Bioenergy and Bioprocess Technology

Xiaoquan Su

Nanchang University

Maozhen Han

Anhui Provincial Hospital

Xue Zhu

Ningbo Institute of Industrial Technology

Zhi Wang

Chinese Academy of Sciences

Pengshuo Yang

Huazhong University of Science and Technology

Lei Ji

Chinese Academy of Medical Sciences & Peking Union Medical College

Xiaoguo Li

First Hospital of Lanzhou University

Xiaolong Qi

Zhongda Hospital Southeast University

Yanna Liu

Dalian Medical University

Cooperative Institutions

Chinese Academy of Sciences

Huazhong University of Science and Technology

University of Chinese Academy of Sciences

Chinese Academy of Medical Sciences & Peking Union Medical College

Southern Medical University

China Agricultural University

Peking University

Qingdao Institute of Bioenergy and Bioprocess Technology

Nanjing Medical University

Zhejiang University

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Heterogeneous circRNA expression profiles and regulatory functions among HEK293T single cells

Scientific Reports (2017)

Chaofang Zhong Shaojun Yu Maozhen Han Jiahuan Chen Kang Ning

The single-cell analysis is becoming a powerful method for early detection of the abnormal variant in tissues, especially for profiling a small number of heterogeneous cells. With the advancement of sequencing technologies, many types of non-coding elements including miRNAs and lncRNAs which shed light on their heterogeneous patterns and functions among cells, have been profiled at the single-cell level. However, the complete picture of circRNA profile at single-cell level is still lacking. In this study, RNA-Seq data obtained from single HEK293T cells have been used to analyze expressions and functions of heterogeneous circRNA profiles. The enrichment patterns of circRNAs, interactions with miRNAs and pathways such as ErbB signaling pathway and protein processing in endoplasmic reticulum, have also been investigated. The results showed that circRNAs had a specific distribution pattern which was implicated with expression, miRNA and functional profiles at single-cell level. This assessment study of the expressions and functions of circRNAs at single-cell level shed light on heterogeneities among single cells.

HEK 293 cells

Single-Cell Analysis

Cell type

10.1038/s41598-017-14807-w

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Citations (7)

Health-oriented strategies are needed to optimize China’s 2025 clean air action plan

Science Bulletin (2024)

Tao Xue Kang Ning Wei Wan Tong Zhu

Action plan

10.1016/j.scib.2024.05.019

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Citations (1)

Linkage and driving mechanisms of antibiotic resistome in surface and ground water: Their responses to land use and seasonal variation

Water Research (2022)

Lu Zhang Lei Ji Xi Liu Xue Zhu Kang Ning

Wet season

Resistome

Dry season

10.1016/j.watres.2022.118279

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Citations (46)

Global Characterization of Differential Gene Expression Profiles in Mouse Vγ1+ and Vγ4+ γδ T Cells

PLoS ONE (2014)

Peng Dong Siya Zhang Menghua Cai Kang Ning Yu Hu

Peripheral γδ T cells in mice are classified into two major subpopulations, Vγ1+ and Vγ4+, based on the composition of T cell receptors. However, their intrinsic differences remain unclear. In this study, we analyzed gene expression profiles of the two subsets using Illumina HiSeq 2000 Sequencer. We identified 1995 transcripts related to the activation of Vγ1+ γδ T cells, and 2158 transcripts related to the activation of Vγ4+ γδ T cells. We identified 24 transcripts differentially expressed between the two subsets in resting condition, and 20 after PMA/Ionomycin treatment. We found that both cell types maintained phenotypes producing IFN-γ, TNF-α, TGF-β and IL-10. However, Vγ1+ γδ T cells produced more Th2 type cytokines, such as IL-4 and IL-5, while Vγ4+ γδ T cells preferentially produced IL-17. Our study provides a comprehensive gene expression profile of mouse peripheral Vγ1+ and Vγ4+ γδ T cells that describes the inherent differences between them.

Ionomycin

10.1371/journal.pone.0112964

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Citations (14)

Three‐step integrated process for isolation and purification of impurities in drug substance by recycling chromatography

AIChE Journal (2024)

Guangxia Jin Yuxue Wu Jiarong Sang Feng Wei Kang Ning

Abstract This work reported the application of a twin‐column recycling chromatography system for the separation of three minor impurities in crude aloe‐emodin. The whole process went through three steps, each using a different mobile phase to separate corresponding impurity, which were integrated and automatically operated in a single device. Despite these impurities peaked closely in high‐performance liquid chromatography, they were successfully purified to a content exceeding 97%. In addition, the lab‐scale separation could reach the yields at the mg‐level. The high efficacy should be mainly attributed to the introduction of a small step solvent gradient between the upstream and downstream columns, which helped to counterbalance the band broadening. This report suggested that such an automated chromatographic system could provide fast and accurate separation of multiple impurities, allow the process of high‐throughput samples, and reduce the time required for purification and recovery of minor impurities in drugs.

Isolation

10.1002/aic.18597

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Citations (0)

Assessment of quality control approaches for metagenomic data analysis

Scientific Reports (2014)

Qian Zhou Xiaoquan Su Kang Ning

Currently there is an explosive increase of the next-generation sequencing (NGS) projects and related datasets, which have to be processed by Quality Control (QC) procedures before they could be utilized for omics analysis. QC procedure usually includes identification and filtration of sequencing artifacts such as low-quality reads and contaminating reads, which would significantly affect and sometimes mislead downstream analysis. Quality control of NGS data for microbial communities is especially challenging. In this work, we have evaluated and compared the performance and effects of various QC pipelines on different types of metagenomic NGS data and from different angles, based on which general principles of using QC pipelines were proposed. Results based on both simulated and real metagenomic datasets have shown that: firstly, QC-Chain is superior in its ability for contamination identification for metagenomic NGS datasets with different complexities with high sensitivity and specificity. Secondly, the high performance computing engine enabled QC-Chain to achieve a significant reduction in processing time compared to other pipelines based on serial computing. Thirdly, QC-Chain could outperform other tools in benefiting downstream metagenomic data analysis.

Identification

10.1038/srep06957

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Citations (56)

MetaSee: An Interactive and Extendable Visualization Toolbox for Metagenomic Sample Analysis and Comparison

PLoS ONE (2012)

Baoxing Song Xiaoquan Su Jian Xu Kang Ning

The NGS (next generation sequencing)-based metagenomic data analysis is becoming the mainstream for the study of microbial communities. Faced with a large amount of data in metagenomic research, effective data visualization is important for scientists to effectively explore, interpret and manipulate such rich information. The visualization of the metagenomic data, especially multi-sample data, is one of the most critical challenges. The different data sample sources, sequencing approaches and heterogeneous data formats make robust and seamless data visualization difficult. Moreover, researchers have different focuses on metagenomic studies: taxonomical or functional, sample-centric or genome-centric, single sample or multiple samples, etc. However, current efforts in metagenomic data visualization cannot fulfill all of these needs, and it is extremely hard to organize all of these visualization effects in a systematic manner. An extendable, interactive visualization tool would be the method of choice to fulfill all of these visualization needs. In this paper, we have present MetaSee, an extendable toolbox that facilitates the interactive visualization of metagenomic samples of interests. The main components of MetaSee include: (I) a core visualization engine that is composed of different views for comparison of multiple samples: Global view, Phylogenetic view, Sample view and Taxa view, as well as link-out for more in-depth analysis; (II) front-end user interface with real metagenomic models that connect to the above core visualization engine and (III) open-source portal for the development of plug-ins for MetaSee. This integrative visualization tool not only provides the visualization effects, but also enables researchers to perform in-depth analysis of the metagenomic samples of interests. Moreover, its open-source portal allows for the design of plug-ins for MetaSee, which would facilitate the development of any additional visualization effects.

Toolbox

Sample (material)

Interactive Visualization

10.1371/journal.pone.0048998

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Citations (18)

Meta-Prism 2.0: Enabling algorithm and web server for ultra-fast, memory-efficient, and accurate analysis among millions of microbial community samples

GigaScience (2022)

Kai Kang Hui Chong Kang Ning

Microbial community samples have been accumulating at a speed faster than ever, with hundreds of thousands of samples been sequenced each year. Mining such a huge amount of multisource heterogeneous data is becoming an increasingly difficult challenge, so efficient and accurate compare and search of samples is in urgent need: faced with millions of samples in the data repository, traditional sample comparison and search approaches fall short in speed and accuracy.

Prism

Sample (material)

10.1093/gigascience/giac073

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Citations (1)

TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations

Scientific Reports (2017)

Runzhi Zhang Shaojun Yu Hong Bai Kang Ning

Abstract With the advancement of systems biology research, we have already seen great progress in pharmacology studies, especially in network pharmacology. Network pharmacology has been proven to be effective for establishing the “compounds-proteins/genes-diseases” network, and revealing the regulation principles of small molecules in a high-throughput manner, thus would be very effective for the analysis of drug combinations, especially for TCM preparations. In this work, we have proposed the TCM-Mesh system, which records TCM-related information collected from various resources and could serve for network pharmacology analysis for TCM preparations in a high-throughput manner (http://mesh.tcm.microbioinformatics.org/). Currently, the database contains 6,235 herbs, 383,840 compounds, 14,298 genes, 6,204 diseases, 144,723 gene-disease associations, 3,440,231 pairs of gene interactions, 163,221 side effect records and 71 toxic records, and web-based software construct a network between herbs and treated diseases, which will help to understand the underlying mechanisms for TCM preparations at molecular levels. We have used 1,293 FDA-approved drugs, as well as compounds from an herbal material Panax ginseng and a patented drug Liuwei Dihuang Wan (LDW) for evaluating our database. By comparison of different databases, as well as checking against literature, we have demonstrated the completeness, effectiveness, and accuracy of our database.

Systems pharmacology

10.1038/s41598-017-03039-7

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Citations (205)

Decoding the link of microbiome niches with homologous sequences enables accurately targeted protein structure prediction

Proceedings of the National Academy of Sciences (2021)

Pengshuo Yang Wei Zheng Kang Ning Yang Zhang

Significance Metagenome sequencing provides a useful repository to extract evolutionary information and assist protein structure predictions. The sequence-search process, however, becomes increasingly prohibitive due to the huge library size. We hypothesize that there exist inherent evolutionary linkages between microbial niches and protein families that can be used to construct precise multiple sequence alignments (MSAs). To examine the hypothesis, we built a model library of four major biomes containing 4.25 billion sequences. Large-scale protein folding experiments revealed that MSAs collected from individually linked microbiomes can generate more accurate contact and structure models than those from all microbiome sequences but use significantly fewer computing resources. These results demonstrate the potential to solve the metagenome-search problem using a microbiome targeted approach.

Biome

10.1073/pnas.2110828118

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Citations (17)