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Featured researches published by Yu Kang.


Mbio | 2014

Heteroresistance at the Single-Cell Level: Adapting to Antibiotic Stress through a Population-Based Strategy and Growth-Controlled Interphenotypic Coordination

Xiyin Wang; Yu Kang; Chunxiong Luo; T. Zhao; L. Liu; X. Jiang; R. Fu; Shuchang An; Jichao Chen; N. Jiang; Lufeng Ren; Q. Wang; J. K. Baillie; Zhancheng Gao; Jun Yu

ABSTRACT Heteroresistance refers to phenotypic heterogeneity of microbial clonal populations under antibiotic stress, and it has been thought to be an allocation of a subset of “resistant” cells for surviving in higher concentrations of antibiotic. The assumption fits the so-called bet-hedging strategy, where a bacterial population “hedges” its “bet” on different phenotypes to be selected by unpredicted environment stresses. To test this hypothesis, we constructed a heteroresistance model by introducing a blaCTX-M-14 gene (coding for a cephalosporin hydrolase) into a sensitive Escherichia coli strain. We confirmed heteroresistance in this clone and that a subset of the cells expressed more hydrolase and formed more colonies in the presence of ceftriaxone (exhibited stronger “resistance”). However, subsequent single-cell-level investigation by using a microfluidic device showed that a subset of cells with a distinguishable phenotype of slowed growth and intensified hydrolase expression emerged, and they were not positively selected but increased their proportion in the population with ascending antibiotic concentrations. Therefore, heteroresistance—the gradually decreased colony-forming capability in the presence of antibiotic—was a result of a decreased growth rate rather than of selection for resistant cells. Using a mock strain without the resistance gene, we further demonstrated the existence of two nested growth-centric feedback loops that control the expression of the hydrolase and maximize population growth in various antibiotic concentrations. In conclusion, phenotypic heterogeneity is a population-based strategy beneficial for bacterial survival and propagation through task allocation and interphenotypic collaboration, and the growth rate provides a critical control for the expression of stress-related genes and an essential mechanism in responding to environmental stresses. IMPORTANCE Heteroresistance is essentially phenotypic heterogeneity, where a population-based strategy is thought to be at work, being assumed to be variable cell-to-cell resistance to be selected under antibiotic stress. Exact mechanisms of heteroresistance and its roles in adaptation to antibiotic stress have yet to be fully understood at the molecular and single-cell levels. In our study, we have not been able to detect any apparent subset of “resistant” cells selected by antibiotics; on the contrary, cell populations differentiate into phenotypic subsets with variable growth statuses and hydrolase expression. The growth rate appears to be sensitive to stress intensity and plays a key role in controlling hydrolase expression at both the bulk population and single-cell levels. We have shown here, for the first time, that phenotypic heterogeneity can be beneficial to a growing bacterial population through task allocation and interphenotypic collaboration other than partitioning cells into different categories of selective advantage. Heteroresistance is essentially phenotypic heterogeneity, where a population-based strategy is thought to be at work, being assumed to be variable cell-to-cell resistance to be selected under antibiotic stress. Exact mechanisms of heteroresistance and its roles in adaptation to antibiotic stress have yet to be fully understood at the molecular and single-cell levels. In our study, we have not been able to detect any apparent subset of “resistant” cells selected by antibiotics; on the contrary, cell populations differentiate into phenotypic subsets with variable growth statuses and hydrolase expression. The growth rate appears to be sensitive to stress intensity and plays a key role in controlling hydrolase expression at both the bulk population and single-cell levels. We have shown here, for the first time, that phenotypic heterogeneity can be beneficial to a growing bacterial population through task allocation and interphenotypic collaboration other than partitioning cells into different categories of selective advantage.


Nucleic Acids Research | 2016

Precision methylome characterization of Mycobacterium tuberculosis complex (MTBC) using PacBio single-molecule real-time (SMRT) technology

Lingxiang Zhu; Jun Zhong; Xinmiao Jia; Guan Liu; Yu Kang; Mengxing Dong; Xiuli Zhang; Qian Li; Liya Yue; C. R. Li; Jing Fu; Jingfa Xiao; Jiangwei Yan; Bing Zhang; Meng Lei; Suting Chen; Lingna Lv; Baoli Zhu; Hairong Huang; Fei Chen

Tuberculosis (TB) remains one of the most common infectious diseases caused by Mycobacterium tuberculosis complex (MTBC). To panoramically analyze MTBCs genomic methylation, we completed the genomes of 12 MTBC strains (Mycobacterium bovis; M. bovis BCG; M. microti; M. africanum; M. tuberculosis H37Rv; H37Ra; and 6 M. tuberculosis clinical isolates) belonging to different lineages and characterized their methylomes using single-molecule real-time (SMRT) technology. We identified three m6A sequence motifs and their corresponding methyltransferase (MTase) genes, including the reported mamA, hsdM and a newly discovered mamB. We also experimentally verified the methylated motifs and functions of HsdM and MamB. Our analysis indicated the MTase activities varied between 12 strains due to mutations/deletions. Furthermore, through measuring ‘the methylated-motif-site ratio’ and ‘the methylated-read ratio’, we explored the methylation status of each modified site and sequence-read to obtain the ‘precision methylome’ of the MTBC strains, which enabled intricate analysis of MTase activity at whole-genome scale. Most unmodified sites overlapped with transcription-factor binding-regions, which might protect these sites from methylation. Overall, our findings show enormous potential for the SMRT platform to investigate the precise character of methylome, and significantly enhance our understanding of the function of DNA MTase.


BMC Genomics | 2016

An integrative and applicable phylogenetic footprinting framework for cis-regulatory motifs identification in prokaryotic genomes

Bingqiang Liu; Hanyuan Zhang; Chuan Zhou; Guojun Li; Anne Fennell; Guanghui Wang; Yu Kang; Qi Liu; Qin Ma

BackgroundPhylogenetic footprinting is an important computational technique for identifying cis-regulatory motifs in orthologous regulatory regions from multiple genomes, as motifs tend to evolve slower than their surrounding non-functional sequences. Its application, however, has several difficulties for optimizing the selection of orthologous data and reducing the false positives in motif prediction.ResultsHere we present an integrative phylogenetic footprinting framework for accurate motif predictions in prokaryotic genomes (MP3). The framework includes a new orthologous data preparation procedure, an additional promoter scoring and pruning method and an integration of six existing motif finding algorithms as basic motif search engines. Specifically, we collected orthologous genes from available prokaryotic genomes and built the orthologous regulatory regions based on sequence similarity of promoter regions. This procedure made full use of the large-scale genomic data and taxonomy information and filtered out the promoters with limited contribution to produce a high quality orthologous promoter set. The promoter scoring and pruning is implemented through motif voting by a set of complementary predicting tools that mine as many motif candidates as possible and simultaneously eliminate the effect of random noise. We have applied the framework to Escherichia coli k12 genome and evaluated the prediction performance through comparison with seven existing programs. This evaluation was systematically carried out at the nucleotide and binding site level, and the results showed that MP3 consistently outperformed other popular motif finding tools. We have integrated MP3 into our motif identification and analysis server DMINDA, allowing users to efficiently identify and analyze motifs in 2,072 completely sequenced prokaryotic genomes.ConclusionThe performance evaluation indicated that MP3 is effective for predicting regulatory motifs in prokaryotic genomes. Its application may enhance progress in elucidating transcription regulation mechanism, thus provide benefit to the genomic research community and prokaryotic genome researchers in particular.


Mbio | 2014

Flexibility and Symmetry of Prokaryotic Genome Rearrangement Reveal Lineage-Associated Core-Gene-Defined Genome Organizational Frameworks

Yu Kang; Chaohao Gu; Lina Yuan; Yue Wang; Yanmin Zhu; Xinna Li; Qibin Luo; Jingfa Xiao; Daquan Jiang; Minping Qian; Aftab Ahmed Khan; Fei Chen; Zhang Zhang; Jun Yu

ABSTRACT The prokaryotic pangenome partitions genes into core and dispensable genes. The order of core genes, albeit assumed to be stable under selection in general, is frequently interrupted by horizontal gene transfer and rearrangement, but how a core-gene-defined genome maintains its stability or flexibility remains to be investigated. Based on data from 30 species, including 425 genomes from six phyla, we grouped core genes into syntenic blocks in the context of a pangenome according to their stability across multiple isolates. A subset of the core genes, often species specific and lineage associated, formed a core-gene-defined genome organizational framework (cGOF). Such cGOFs are either single segmental (one-third of the species analyzed) or multisegmental (the rest). Multisegment cGOFs were further classified into symmetric or asymmetric according to segment orientations toward the origin-terminus axis. The cGOFs in Gram-positive species are exclusively symmetric and often reversible in orientation, as opposed to those of the Gram-negative bacteria, which are all asymmetric and irreversible. Meanwhile, all species showing strong strand-biased gene distribution contain symmetric cGOFs and often specific DnaE (α subunit of DNA polymerase III) isoforms. Furthermore, functional evaluations revealed that cGOF genes are hub associated with regard to cellular activities, and the stability of cGOF provides efficient indexes for scaffold orientation as demonstrated by assembling virtual and empirical genome drafts. cGOFs show species specificity, and the symmetry of multisegmental cGOFs is conserved among taxa and constrained by DNA polymerase-centric strand-biased gene distribution. The definition of species-specific cGOFs provides powerful guidance for genome assembly and other structure-based analysis. IMPORTANCE Prokaryotic genomes are frequently interrupted by horizontal gene transfer (HGT) and rearrangement. To know whether there is a set of genes not only conserved in position among isolates but also functionally essential for a given species and to further evaluate the stability or flexibility of such genome structures across lineages are of importance. Based on a large number of multi-isolate pangenomic data, our analysis reveals that a subset of core genes is organized into a core-gene-defined genome organizational framework, or cGOF. Furthermore, the lineage-associated cGOFs among Gram-positive and Gram-negative bacteria behave differently: the former, composed of 2 to 4 segments, have their fragments symmetrically rearranged around the origin-terminus axis, whereas the latter show more complex segmentation and are partitioned asymmetrically into chromosomal structures. The definition of cGOFs provides new insights into prokaryotic genome organization and efficient guidance for genome assembly and analysis. Prokaryotic genomes are frequently interrupted by horizontal gene transfer (HGT) and rearrangement. To know whether there is a set of genes not only conserved in position among isolates but also functionally essential for a given species and to further evaluate the stability or flexibility of such genome structures across lineages are of importance. Based on a large number of multi-isolate pangenomic data, our analysis reveals that a subset of core genes is organized into a core-gene-defined genome organizational framework, or cGOF. Furthermore, the lineage-associated cGOFs among Gram-positive and Gram-negative bacteria behave differently: the former, composed of 2 to 4 segments, have their fragments symmetrically rearranged around the origin-terminus axis, whereas the latter show more complex segmentation and are partitioned asymmetrically into chromosomal structures. The definition of cGOFs provides new insights into prokaryotic genome organization and efficient guidance for genome assembly and analysis.


BMC Genomics | 2017

GAAP: Genome-organization-framework-Assisted Assembly Pipeline for prokaryotic genomes

Lina Yuan; Yang Yu; Yanmin Zhu; Yulai Li; Changqing Li; Rujiao Li; Qin Ma; Gilman K. H. Siu; Jun Yu; Taijiao Jiang; Jingfa Xiao; Yu Kang

BackgroundNext-generation sequencing (NGS) technologies have greatly promoted the genomic study of prokaryotes. However, highly fragmented assemblies due to short reads from NGS are still a limiting factor in gaining insights into the genome biology. Reference-assisted tools are promising in genome assembly, but tend to result in false assembly when the assigned reference has extensive rearrangements.ResultsHerein, we present GAAP, a genome assembly pipeline for scaffolding based on core-gene-defined Genome Organizational Framework (cGOF) described in our previous study. Instead of assigning references, we use the multiple-reference-derived cGOFs as indexes to assist in order and orientation of the scaffolds and build a skeleton structure, and then use read pairs to extend scaffolds, called local scaffolding, and distinguish between true and chimeric adjacencies in the scaffolds. In our performance tests using both empirical and simulated data of 15 genomes in six species with diverse genome size, complexity, and all three categories of cGOFs, GAAP outcompetes or achieves comparable results when compared to three other reference-assisted programs, AlignGraph, Ragout and MeDuSa.ConclusionsGAAP uses both cGOF and pair-end reads to create assemblies in genomic scale, and performs better than the currently available reference-assisted assembly tools as it recovers more assemblies and makes fewer false locations, especially for species with extensive rearranged genomes. Our method is a promising solution for reconstruction of genome sequence from short reads of NGS.


Frontiers in Cellular and Infection Microbiology | 2018

Comparative Whole-Genomic Analysis of an Ancient L2 Lineage Mycobacterium tuberculosis Reveals a Novel Phylogenetic Clade and Common Genetic Determinants of Hypervirulent Strains

Rahim Rajwani; Wing Cheong Yam; Ying Zhang; Yu Kang; Barry Kin Chung Wong; Kenneth Siu-Sing Leung; Kingsley King-Gee Tam; Ketema Tafess Tulu; Li Zhu; Gilman K. H. Siu

Background: Development of improved therapeutics against tuberculosis (TB) is hindered by an inadequate understanding of the relationship between disease severity and genetic diversity of its causative agent, Mycobacterium tuberculosis. We previously isolated a hypervirulent M. tuberculosis strain H112 from an HIV-negative patient with an aggressive disease progression from pulmonary TB to tuberculous meningitis—the most severe manifestation of tuberculosis. Human macrophage challenge experiment demonstrated that the strain H112 exhibited significantly better intracellular survivability and induced lower level of TNF-α than the reference virulent strain H37Rv and other 123 clinical isolates. Aim: The present study aimed to identify the potential genetic determinants of mycobacterial virulence that were common to strain H112 and hypervirulent M. tuberculosis strains of the same phylogenetic clade isolated in other global regions. Methods: A low-virulent M. tuberculosis strain H54 which belonged to the same phylogenetic lineage (L2) as strain H112 was selected from a collection of 115 clinical isolates. Both H112 and H54 were whole-genome-sequenced using PacBio sequencing technology. A comparative genomics approach was adopted to identify mutations present in strain H112 but absent in strain H54. Subsequently, an extensive phylogenetic analysis was conducted by including all publically available M. tuberculosis genomes. Single-nucleotide-polymorphisms (SNPs) and structural variations (SVs) common to hypervirulent strains in the global collection of genomes were considered as potential genetic determinants of hypervirulence. Results:Sequencing data revealed that both H112 and H54 were identified as members of the same sub-lineage L2.2.1. After excluding the lineage-related mutations shared between H112 and H54, we analyzed the phylogenetic relatedness of H112 with global collection of M. tuberculosis genomes (n = 4,338), and identified a novel phylogenetic clade in which four hypervirulent strains isolated from geographically diverse regions were clustered together. All hypervirulent strains in the clade shared 12 SNPs and 5 SVs with H112, including those affecting key virulence-associated loci, notably, a deleterious SNP (rv0178 p. D150E) within mce1 operon and an intergenic deletion (854259_ 854261delCC) in close-proximity to phoP. Conclusion: The present study identified common genetic factors in a novel phylogenetic clade of hypervirulent M. tuberculosis. The causative role of these mutations in mycobacterial virulence should be validated in future study.


Briefings in Bioinformatics | 2017

Bioinformatics tools for quantitative and functional metagenome and metatranscriptome data analysis in microbes

Sheng-Yong Niu; Jinyu Yang; Adam McDermaid; Jing Zhao; Yu Kang; Qin Ma

“This work was supported by the State of South Dakota Research Innovation Center, the Agriculture Experiment Station of South Dakota State University. Support for this project was also provided by the Sanford Health – South Dakota State University Collaborative Research Seed Grant Program. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562.”


Science China-life Sciences | 2013

Complete genome sequence of methicillin-sensitive Staphylococcus aureus containing a heterogeneic staphylococcal cassette chromosome element

Dezhi Li; YaNan Chu; Lufeng Ren; Xingang Li; Lina Yuan; Yu Kang; Wei Zhang; Yu Yang; Xumin Wang; J. Kenneth Baillie; Jun Yu; Zhancheng Gao

Staphylococcus aureus is a common human bacterium that sometimes becomes pathogenic, causing serious infections. A key feature of S. aureus is its ability to acquire resistance to antibiotics. The presence of the staphylococcal cassette chromosome (SCC) element in serotypes of S. aureus has been confirmed using multiplex PCR assays. The SCC element is the only vector known to carry the mecA gene, which encodes methicillin resistance in S. aureus infections. Here, we report the genome sequence of a novel methicillin-sensitive S. aureus (MSSA) strain: SCC-like MSSA463. This strain was originally erroneously serotyped as methicillin-resistant S. aureus in a clinical laboratory using multiplex PCR methods. We sequenced the genome of SCC-like MSSA463 using pyrosequencing techniques and compared it with known genome sequences of other S. aureus isolates. An open reading frame (CZ049; AB037671) was identified downstream of attL and attR inverted repeat sequences. Our results suggest that a lateral gene transfer occurred between S. aureus and other organisms, partially changing S. aureus infectivity. We propose that attL and attR inverted repeats in S. aureus serve as frequent insertion sites for exogenous genes.


BMC Genomics | 2018

PGAP-X: extension on pan-genome analysis pipeline

Yongbing Zhao; Chen Sun; Dongyu Zhao; Yadong Zhang; Yang You; Xinmiao Jia; Junhui Yang; Lingping Wang; Jinyue Wang; Haohuan Fu; Yu Kang; Fei Chen; Jun Yu; Jiayan Wu; Jingfa Xiao


Archive | 2017

Additional file 1: Figure S1. of GAAP: Genome-organization-framework-Assisted Assembly Pipeline for prokaryotic genomes

Lina Yuan; Yang Yu; Yanmin Zhu; Yulai Li; Changqing Li; Rujiao Li; Qin; Gilman K. H. Siu; Jun Yu; Taijiao Jiang; Jingfa Xiao; Yu Kang

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Jun Yu

Beijing Institute of Genomics

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Jingfa Xiao

Beijing Institute of Genomics

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Lina Yuan

Beijing Institute of Genomics

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Fei Chen

Chinese Academy of Sciences

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Yanmin Zhu

Beijing Institute of Genomics

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Qin Ma

South Dakota State University

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Gilman K. H. Siu

Hong Kong Polytechnic University

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Aftab Ahmed Khan

Beijing Institute of Genomics

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