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Article ; Online: RNA 3D Structure Comparison Using RNA-Puzzles Toolkit.

Magnus, Marcin / Miao, Zhichao

Methods in molecular biology (Clifton, N.J.)

2023 Volume 2586, Page(s) 263–285

Abstract: Computational modeling of RNA three-dimensional (3D) structure may help in unrevealing the molecular mechanisms of RNA molecules and in designing molecules with novel functions. An unbiased blind assessment to benchmark the computational modeling is ... ...

Abstract	Computational modeling of RNA three-dimensional (3D) structure may help in unrevealing the molecular mechanisms of RNA molecules and in designing molecules with novel functions. An unbiased blind assessment to benchmark the computational modeling is required to understand the achievements and bottlenecks of the prediction, while a standard structure comparison protocol is necessary. RNA-Puzzles is a community-wide effort on the assessment of blind prediction of RNA tertiary structures. And RNA-Puzzles toolkit is a computational resource derived from RNA-Puzzles, which includes (i) decoy sets generated by different RNA 3D structure prediction methods; (ii) 3D structure normalization, analysis, manipulation, and visualization tools; and (iii) 3D structure comparison metric tools. In this chapter, we illustrate a standard RNA 3D structure prediction assessment protocol using the selected tools from RNA-Puzzles toolkit: rna-tools and RNA_assessment.
MeSH term(s)	RNA/chemistry ; Nucleic Acid Conformation ; Software ; Computer Simulation ; Benchmarking
Chemical Substances	RNA (63231-63-0)
Language	English
Publishing date	2023-01-27
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-0716-2768-6_16
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Benchmarking strategies for cross-species integration of single-cell RNA sequencing data.

Song, Yuyao / Miao, Zhichao / Brazma, Alvis / Papatheodorou, Irene

Nature communications

2023 Volume 14, Issue 1, Page(s) 6495

Abstract: The growing number of available single-cell gene expression datasets from different species creates opportunities to explore evolutionary relationships between cell types across species. Cross-species integration of single-cell RNA-sequencing data has ... ...

Abstract	The growing number of available single-cell gene expression datasets from different species creates opportunities to explore evolutionary relationships between cell types across species. Cross-species integration of single-cell RNA-sequencing data has been particularly informative in this context. However, in order to do so robustly it is essential to have rigorous benchmarking and appropriate guidelines to ensure that integration results truly reflect biology. Here, we benchmark 28 combinations of gene homology mapping methods and data integration algorithms in a variety of biological settings. We examine the capability of each strategy to perform species-mixing of known homologous cell types and to preserve biological heterogeneity using 9 established metrics. We also develop a new biology conservation metric to address the maintenance of cell type distinguishability. Overall, scANVI, scVI and SeuratV4 methods achieve a balance between species-mixing and biology conservation. For evolutionarily distant species, including in-paralogs is beneficial. SAMap outperforms when integrating whole-body atlases between species with challenging gene homology annotation. We provide our freely available cross-species integration and assessment pipeline to help analyse new data and develop new algorithms.
MeSH term(s)	Benchmarking ; Algorithms ; Molecular Sequence Annotation ; Exome Sequencing ; Sequence Analysis, RNA/methods ; Single-Cell Analysis/methods
Language	English
Publishing date	2023-10-14
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-41855-w
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Article ; Online: CATD: a reproducible pipeline for selecting cell-type deconvolution methods across tissues.

Vathrakokoili Pournara, Anna / Miao, Zhichao / Beker, Ozgur Yilimaz / Nolte, Nadja / Brazma, Alvis / Papatheodorou, Irene

Bioinformatics advances

2024 Volume 4, Issue 1, Page(s) vbae048

Abstract: Motivation: Cell-type deconvolution methods aim to infer cell composition from bulk transcriptomic data. The proliferation of developed methods coupled with inconsistent results obtained in many cases, highlights the pressing need for guidance in the ... ...

Abstract	Motivation: Cell-type deconvolution methods aim to infer cell composition from bulk transcriptomic data. The proliferation of developed methods coupled with inconsistent results obtained in many cases, highlights the pressing need for guidance in the selection of appropriate methods. Additionally, the growing accessibility of single-cell RNA sequencing datasets, often accompanied by bulk expression from related samples enable the benchmark of existing methods. Results: In this study, we conduct a comprehensive assessment of 31 methods, utilizing single-cell RNA-sequencing data from diverse human and mouse tissues. Employing various simulation scenarios, we reveal the efficacy of regression-based deconvolution methods, highlighting their sensitivity to reference choices. We investigate the impact of bulk-reference differences, incorporating variables such as sample, study and technology. We provide validation using a gold standard dataset from mononuclear cells and suggest a consensus prediction of proportions when ground truth is not available. We validated the consensus method on data from the stomach and studied its spillover effect. Importantly, we propose the use of the critical assessment of transcriptomic deconvolution (CATD) pipeline which encompasses functionalities for generating references and pseudo-bulks and running implemented deconvolution methods. CATD streamlines simultaneous deconvolution of numerous bulk samples, providing a practical solution for speeding up the evaluation of newly developed methods. Availability and implementation: https://github.com/Papatheodorou-Group/CATD_snakemake.
Language	English
Publishing date	2024-03-23
Publishing country	England
Document type	Journal Article
ISSN	2635-0041
ISSN (online)	2635-0041
DOI	10.1093/bioadv/vbae048
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: NaCl sealing Strategy-Assisted synthesis CoO-Co heterojunctions as efficient oxygen electrocatalysts for Zn air batteries

Diao, Lechen / Zhou, Wei / Zhang, Biao / Shi, Chunsheng / Miao, Zhichao / Zhou, Jin / He, Chunnian

Journal of Colloid And Interface Science. 2023 Sept., v. 645 p.329-337

2023

Abstract: Developing highly efficient, low-cost, and stable bifunctional oxygen electrocatalysts is essential for the wide popularization of rechargeable Zn-air batteries. Combining zero-dimensional metal nanoparticles with two-dimensional metal oxide nanosheets ... ...

Abstract	Developing highly efficient, low-cost, and stable bifunctional oxygen electrocatalysts is essential for the wide popularization of rechargeable Zn-air batteries. Combining zero-dimensional metal nanoparticles with two-dimensional metal oxide nanosheets is an appealing strategy to balance performance and cost. However, the precise construction of these composites remains a great challenge, and their interaction mechanisms lack thorough study. Herein, a cobalt-oxide-based bifunctional oxygen electrocatalyst comprising a rich Co-CoO heterointerface (CoO/Co@NG) was synthesized via a NaCl sealing-assisted pyrolysis strategy. The NaCl crystals played the role of a closed nanoreactor, which facilitated the formation of a CoO-Co heterojunction. Experimental results and theoretical calculations confirmed that the ingeniously constructed heterojunction expedited the oxygen reduction reaction and oxygen evolution reaction kinetics, which is superior to Pt/C. When serving as the air electrode in an assembled liquid-state Zn-air battery, the battery shows high power density (215 mW cm⁻²), specific capacity (710 mAh gzₙ⁻¹), and outstanding durability (720 h at 10 mA cm⁻²). This work provides an innovative avenue to design high-performance heterojunction electrocatalysts for perdurable Zn-air batteries.
Keywords	air ; batteries ; durability ; electrochemistry ; electrodes ; nanoparticles ; nanosheets ; oxygen ; oxygen production ; pyrolysis ; reaction kinetics ; 0D/2D heterostructure electrocatalysts ; Zn-air battery ; Cobalt-oxide based electrocatalyst ; Oxygen reduction reaction
Language	English
Dates of publication	2023-09
Size	p. 329-337.
Publishing place	Elsevier Inc.
Document type	Article ; Online
ZDB-ID	241597-5
ISSN	1095-7103 ; 0021-9797
ISSN (online)	1095-7103
ISSN	0021-9797
DOI	10.1016/j.jcis.2023.04.080
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: NaCl sealing Strategy-Assisted synthesis CoO-Co heterojunctions as efficient oxygen electrocatalysts for Zn air batteries.

Diao, Lechen / Zhou, Wei / Zhang, Biao / Shi, Chunsheng / Miao, Zhichao / Zhou, Jin / He, Chunnian

Journal of colloid and interface science

2023 Volume 645, Page(s) 329–337

Abstract	Developing highly efficient, low-cost, and stable bifunctional oxygen electrocatalysts is essential for the wide popularization of rechargeable Zn-air batteries. Combining zero-dimensional metal nanoparticles with two-dimensional metal oxide nanosheets is an appealing strategy to balance performance and cost. However, the precise construction of these composites remains a great challenge, and their interaction mechanisms lack thorough study. Herein, a cobalt-oxide-based bifunctional oxygen electrocatalyst comprising a rich Co-CoO heterointerface (CoO/Co@NG) was synthesized via a NaCl sealing-assisted pyrolysis strategy. The NaCl crystals played the role of a closed nanoreactor, which facilitated the formation of a CoO-Co heterojunction. Experimental results and theoretical calculations confirmed that the ingeniously constructed heterojunction expedited the oxygen reduction reaction and oxygen evolution reaction kinetics, which is superior to Pt/C. When serving as the air electrode in an assembled liquid-state Zn-air battery, the battery shows high power density (215 mW cm
Language	English
Publishing date	2023-04-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	241597-5
ISSN	1095-7103 ; 0021-9797
ISSN (online)	1095-7103
ISSN	0021-9797
DOI	10.1016/j.jcis.2023.04.080
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Article ; Online: A N-doped carbon-supported In

Zhang, Jie / Liang, Manfen / Xu, Haimei / Huang, Hong / Meng, Jian / Mu, Jinglin / Miao, Zhichao / Zhou, Jin

Chemical communications (Cambridge, England)

2024 Volume 60, Issue 12, Page(s) 1587–1590

Abstract: ... A novel ... ...

Abstract	A novel In
Language	English
Publishing date	2024-02-06
Publishing country	England
Document type	Journal Article
ZDB-ID	1472881-3
ISSN	1364-548X ; 1359-7345 ; 0009-241X
ISSN (online)	1364-548X
ISSN	1359-7345 ; 0009-241X
DOI	10.1039/d3cc05872g
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Interface-Engineered 3D porous MoS

Diao, Lechen / Wang, Pingping / Feng, Guozhou / Zhang, Biao / Miao, Zhichao / Xu, Li-Ping / Zhou, Jin

Journal of colloid and interface science

2024 Volume 661, Page(s) 957–965

Abstract: Constructing in-plane heterojunctions with high interfacial density using two-dimensional materials represents a promising yet challenging avenue for enhancing the hydrogen evolution reaction (HER) in water electrolysis. In this work, we report that ... ...

Abstract	Constructing in-plane heterojunctions with high interfacial density using two-dimensional materials represents a promising yet challenging avenue for enhancing the hydrogen evolution reaction (HER) in water electrolysis. In this work, we report that three-dimensional porous MoS
Language	English
Publishing date	2024-02-06
Publishing country	United States
Document type	Journal Article
ZDB-ID	241597-5
ISSN	1095-7103 ; 0021-9797
ISSN (online)	1095-7103
ISSN	0021-9797
DOI	10.1016/j.jcis.2024.02.056
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Advances in RNA 3D Structure Modeling Using Experimental Data.

Li, Bing / Cao, Yang / Westhof, Eric / Miao, Zhichao

Frontiers in genetics

2020 Volume 11, Page(s) 574485

Abstract: RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific ... ...

Abstract	RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data.
Keywords	covid19
Language	English
Publishing date	2020-10-26
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2020.574485
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Secondary structure of the SARS-CoV-2 5'-UTR.

Miao, Zhichao / Tidu, Antonin / Eriani, Gilbert / Martin, Franck

RNA biology

2020 Volume 18, Issue 4, Page(s) 447–456

Abstract: The SARS-CoV-2, a positive-sense single-stranded RNA Coronavirus, is a global threat to human health. Thus, understanding its life cycle mechanistically would be important to facilitate the design of antiviral drugs. A key aspect of viral progression is ... ...

Abstract	The SARS-CoV-2, a positive-sense single-stranded RNA Coronavirus, is a global threat to human health. Thus, understanding its life cycle mechanistically would be important to facilitate the design of antiviral drugs. A key aspect of viral progression is the synthesis of viral proteins by the ribosome of the human host. In Coronaviruses, this process is regulated by the viral 5' and 3' untranslated regions (UTRs), but the precise regulatory mechanism has not yet been well understood. In particular, the 5'-UTR of the viral genome is most likely involved in translation initiation of viral proteins. Here, we performed inline probing and RNase V1 probing to establish a model of the secondary structure of SARS-CoV-2 5'-UTR. We found that the 5'-UTR contains stable structures including a very stable four-way junction close to the AUG start codon. Sequence alignment analysis of SARS-CoV-2 variants 5'-UTRs revealed a highly conserved structure with few co-variations that confirmed our secondary structure model based on probing experiments.
MeSH term(s)	5' Untranslated Regions ; Codon, Terminator ; Endoribonucleases/chemistry ; Endoribonucleases/metabolism ; Nucleic Acid Conformation ; RNA, Viral/chemistry ; RNA, Viral/metabolism ; SARS-CoV-2/genetics ; Viral Nonstructural Proteins/genetics
Chemical Substances	5' Untranslated Regions ; Codon, Terminator ; NSP1 protein, SARS-CoV-2 ; RNA, Viral ; Viral Nonstructural Proteins ; Endoribonucleases (EC 3.1.-) ; ribonuclease V(1) (EC 3.1.27.-)
Keywords	covid19
Language	English
Publishing date	2020-09-23
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2159587-2
ISSN	1555-8584 ; 1555-8584
ISSN (online)	1555-8584
ISSN	1555-8584
DOI	10.1080/15476286.2020.1814556
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Evaluation of the stereochemical quality of predicted RNA 3D models in the RNA-Puzzles submissions.

Carrascoza, Francisco / Antczak, Maciej / Miao, Zhichao / Westhof, Eric / Szachniuk, Marta

RNA (New York, N.Y.)

2021 Volume 28, Issue 2, Page(s) 250–262

Abstract: In silico prediction is a well-established approach to derive a general shape of an RNA molecule based on its sequence or secondary structure. This paper reports an analysis of the stereochemical quality of the RNA three-dimensional models predicted ... ...

Abstract	In silico prediction is a well-established approach to derive a general shape of an RNA molecule based on its sequence or secondary structure. This paper reports an analysis of the stereochemical quality of the RNA three-dimensional models predicted using dedicated computer programs. The stereochemistry of 1052 RNA 3D structures, including 1030 models predicted by fully automated and human-guided approaches within 22 RNA-Puzzles challenges and reference structures, is analyzed. The evaluation is based on standards of RNA stereochemistry that the Protein Data Bank requires from deposited experimental structures. Deviations from standard bond lengths and angles, planarity, or chirality are quantified. A reduction in the number of such deviations should help in the improvement of RNA 3D structure modeling approaches.
MeSH term(s)	Animals ; Humans ; Molecular Dynamics Simulation/standards ; Nucleic Acid Conformation ; RNA/chemistry
Chemical Substances	RNA (63231-63-0)
Language	English
Publishing date	2021-11-24
Publishing country	United States
Document type	Evaluation Study ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1241540-6
ISSN	1469-9001 ; 1355-8382
ISSN (online)	1469-9001
ISSN	1355-8382
DOI	10.1261/rna.078685.121
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