SGMFQP: An ontology-based Swine Gut Microbiota Federated Query Platform

Wang, Ying; Jiang, Qin; Geng, Yilin; Hu, Yuren; Tang, Yue; Li, Jixiang; Zhang, Junmei; Mayer, Wolfgang; Liu, Shanmei; Zhang, Hongyu; Yan, Xianghua; Feng, Zaiwen

doi:10.1016/j.ymeth.2023.02.010

Cited by 4 publications

(5 citation statements)

References 26 publications

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Section: Resultsmentioning

confidence: 99%

“…We developed a vinculin-null mouse embryonic fibroblast ( Vcl KO MEF) cell line 17 , stably expressing paxillin-GFP. Consistent with prior findings, vinculin absence did not impede focal adhesion formation or maturation (Figure 4A) 17,41 . However, our observations revealed that Vcl KO cells predominantly maintained an integrin force around 7 pN (Figure 4B), with a substantial decrease in integrins capable of exerting forces beyond 17 pN.…”

Section: Resultsmentioning

confidence: 99%

“…Over the past decade, various types of immobilized molecular fluorescent tension probes have emerged as a revolutionary tool in mechanobiology, providing a detailed lens through which the magnitude of cellular forces can be observed and quantified at the molecular level [6][7][8][9][10][11][12] . Notable examples include the elucidation of integrin-mediated force transduction 8,10,13,14 , the dynamics of T-cell receptor (TCR) forces 15,16 , and the mechanisms underlying cellular rigidity sensing 17 . These studies have not only quantified the magnitude characteristics of cellular forces but have also underscored their pivotal role in driving the mechanisms of mechanical force transduction.…”

Section: Introductionmentioning

confidence: 99%

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DNA-based ForceChrono Probes for Deciphering Single-Molecule Force Dynamics in Living Cells

Hu,

Li,

Zhang

et al. 2024

Preprint

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Accurate measurement of mechanical forces in cells is key to understanding how cells sense and respond to mechanical stimuli, a central aspect of mechanobiology. However, accurately quantifying dynamic forces at the single-molecule level in living cells is a significant challenge. Here, we've developed the DNA-based ForceChrono probe to enable in-depth studies of integrin force dynamics at the single-molecule level in living cells. By illuminating two distinct mechanical points and circumventing the inherent fluctuations of single-molecule fluorescence, the ForceChrono probe enables analysis of the complex dynamics of mechanical forces at the single-molecule level, such as loading rates and durations. Our results refine previous broad estimates of cellular loading rates to a more precise range of 0.5 to 2 pN/s, shedding light on the specifics of cellular mechanics. In addition, this study reveals a critical link between the magnitude and duration of integrin forces, consistent with the catch-bond behavior demonstrated in vitro. The ForceChrono probe has distinct advantages, such as precise analysis of single-molecule force dynamics and robust resistance to fluorescence fluctuations, which will significantly advance our understanding of cell adhesion and mechanotransduction at the single-molecule level.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

DNA-based ForceChrono Probes for Deciphering Single-Molecule Force Dynamics in Living Cells

Hu,

Li,

Zhang

et al. 2024

Preprint

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“…This study refined the pig intestinal microbiota domain ontology, based on the previous ontology of swine gut microbiota used for federal queries 26 , we have developed a more comprehensive and versatile framework, which defined a wider range of concepts and more comprehensive applications. The ontology is mainly used to solve the interoperability between heterogeneous data from multiple sources 27 , and has also been increasingly employed in agricultural field.…”

Section: Discussionmentioning

confidence: 99%

Knowledge graph-derived feed efficiency analysis via pig intestinal microbiota

Zhang,

Jiang,

et al. 2024

Preprint

Self Cite

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Feed efficiency (FE) is essential for pig production, has been reported to be partially explained by gut microbiota. Despite an extensive body of research literature to this topic, studies regarding the regulation of feed efficiency by intestinal microbiota remain fragmented and mostly confined to disorganized or semi-structured unrestricted texts. Meanwhile, structured databases for microbiota analysis are available, yet they often lack a comprehensive understanding of the associated biological processes. Therefore, we have devised an approach to construct a comprehensive knowledge graph by combining unstructured textual intelligence with structured database information and applied it to investigate the relationship between pig intestinal microbes and FE. Firstly, we created the pimReading knowledge base and the domain ontology of pig gut microbiota by annotating, extracting, and integrating semantic information from 157 scientific publications. Secondly, we created the pimPubtator by utilizing PubTator to expand the semantic information related to microbiota. Thirdly, we created the pimDatabase by mapping and combining the ADDAGMA, gutMGene, and KEGG databases based on the ontology. These three knowledge bases were integrated to form the Pig Intestinal Microbial Knowledge Graph (PIMKG). Additionally, we created three biological query cases to validate the performance of PIMKG. These cases not only allow us to identify microbes with the most significant impact on FE but also provide insights into the metabolites produced by these microbes and the associated metabolic pathways. This study introduces PIMKG, mapping key microbes in pig feed efficiency and guiding microbiota-targeted optimization.

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“…This study refined the pig gut microbiota domain ontology, based on the previous ontology of swine gut microbiota used for federal queries 39 , we have developed a more comprehensive and versatile framework, which defined a wider range of concepts and more comprehensive applications. The ontology is mainly used to solve the interoperability between heterogeneous data from multiple sources 40 , and has also been increasingly employed in agricultural field.…”

Section: Discussionmentioning

confidence: 99%

Knowledge graph-derived feed efficiency analysis via pig gut microbiota

Zhang,

Jiang,

et al. 2024

Sci Rep

Self Cite

View full text Add to dashboard Cite

Feed efficiency (FE) is essential for pig production, has been reported to be partially explained by gut microbiota. Despite an extensive body of research literature to this topic, studies regarding the regulation of feed efficiency by gut microbiota remain fragmented and mostly confined to disorganized or semi-structured unrestricted texts. Meanwhile, structured databases for microbiota analysis are available, yet they often lack a comprehensive understanding of the associated biological processes. Therefore, we have devised an approach to construct a comprehensive knowledge graph by combining unstructured textual intelligence with structured database information and applied it to investigate the relationship between pig gut microbes and FE. Firstly, we created the pgmReading knowledge base and the domain ontology of pig gut microbiota by annotating, extracting, and integrating semantic information from 157 scientific publications. Secondly, we created the pgmPubtator by utilizing PubTator to expand the semantic information related to microbiota. Thirdly, we created the pgmDatabase by mapping and combining the ADDAGMA, gutMGene, and KEGG databases based on the ontology. These three knowledge bases were integrated to form the Pig Gut Microbial Knowledge Graph (PGMKG). Additionally, we created five biological query cases to validate the performance of PGMKG. These cases not only allow us to identify microbes with the most significant impact on FE but also provide insights into the metabolites produced by these microbes and the associated metabolic pathways. This study introduces PGMKG, mapping key microbes in pig feed efficiency and guiding microbiota-targeted optimization.

show abstract

SGMFQP: An ontology-based Swine Gut Microbiota Federated Query Platform

Cited by 4 publications

References 26 publications

DNA-based ForceChrono Probes for Deciphering Single-Molecule Force Dynamics in Living Cells

DNA-based ForceChrono Probes for Deciphering Single-Molecule Force Dynamics in Living Cells

Knowledge graph-derived feed efficiency analysis via pig intestinal microbiota

Knowledge graph-derived feed efficiency analysis via pig gut microbiota

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