Multiple interactions of the dynein-2 complex with the IFT-B complex are required for effective intraflagellar transport DOI Creative Commons

Shunya Hiyamizu,

Hantian Qiu,

Laura Vuolo

et al.

Journal of Cell Science, Journal Year: 2023, Volume and Issue: 136(5)

Published: Jan. 12, 2023

ABSTRACT The dynein-2 complex must be transported anterogradely within cilia to then drive retrograde trafficking of the intraflagellar transport (IFT) machinery containing IFT-A and IFT-B complexes. Here, we screened for potential interactions between complexes found multiple among subunits. In particular, WDR60 (also known as DYNC2I1) DYNC2H1–DYNC2LI1 dimer from dynein-2, IFT54 TRAF3IP1) IFT57 contribute dynein-2–IFT-B interactions. interacts with via a conserved region N-terminal its light chain-binding regions. Expression constructs in WDR60-knockout (KO) cells revealed that truncation mutants lacking IFT54-binding site fail rescue abnormal phenotypes WDR60-KO cells, such aberrant accumulation IFT around ciliary tip on distal side transition zone. However, construct specifically just substantially restored defects. line current docking model anterograde trains, these results indicate extensive involving subunits participate their connection.

Language: Английский

Protein-based bioactive coatings: from nanoarchitectonics to applications DOI
Chengyu Fu,

Zhengge Wang,

Xingyu Zhou

et al.

Chemical Society Reviews, Journal Year: 2024, Volume and Issue: 53(3), P. 1514 - 1551

Published: Jan. 1, 2024

Assembly strategy and application direction of protein-based bioactive coatings.

Language: Английский

Citations

24

Current and future directions in network biology DOI Creative Commons
Marinka Žitnik, Michelle M. Li, A. V. Wells

et al.

Bioinformatics Advances, Journal Year: 2024, Volume and Issue: 4(1)

Published: Jan. 1, 2024

Abstract Summary Network biology is an interdisciplinary field bridging computational and biological sciences that has proved pivotal in advancing the understanding of cellular functions diseases across systems scales. Although been around for two decades, it remains nascent. It witnessed rapid evolution, accompanied by emerging challenges. These stem from various factors, notably growing complexity volume data together with increased diversity types describing different tiers organization. We discuss prevailing research directions network biology, focusing on molecular/cellular networks but also other such as biomedical knowledge graphs, patient similarity networks, brain social/contact relevant to disease spread. In more detail, we highlight areas inference comparison multimodal integration heterogeneous higher-order analysis, machine learning network-based personalized medicine. Following overview recent breakthroughs these five areas, offer a perspective future biology. Additionally, scientific communities, educational initiatives, importance fostering within field. This article establishes roadmap immediate long-term vision Availability implementation Not applicable.

Language: Английский

Citations

19

Mass-spectrometry-based proteomics: from single cells to clinical applications DOI
Tiannan Guo, Judith A. Steen, Matthias Mann

et al.

Nature, Journal Year: 2025, Volume and Issue: 638(8052), P. 901 - 911

Published: Feb. 26, 2025

Language: Английский

Citations

3

Recent advances in isobaric labeling and applications in quantitative proteomics DOI

Michael K. Sivanich,

Ting‐Jia Gu, Dylan Nicholas Tabang

et al.

PROTEOMICS, Journal Year: 2022, Volume and Issue: 22(19-20)

Published: June 10, 2022

Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass (LC-MS) can be used to determine abundances proteins and peptides in complex biological samples. Several methods have been developed adapted for accurate quantification based on chemical isotopic labeling. Among various labeling techniques, isobaric tagging approaches rely analysis from MS2-based rather than MS1-based quantification. In this review, we will provide an overview several tags along with some recent developments including complementary ion tags, improvements sensitive quantitation analytes lower abundance, strategies increase multiplexing capabilities, targeted strategies. We also discuss limitations alleviate these restrictions through bioinformatic tools data acquisition methods. This review highlight applications biomarker discovery validation, thermal proteome profiling, cross-linking structural investigations, single-cell analysis, top-down proteomics, different molecules neuropeptides, glycans, metabolites, lipids, while providing considerations evaluations each application.

Language: Английский

Citations

56

Recent advances in predicting and modeling protein–protein interactions DOI

Jesse Durham,

Jing Zhang, Ian R. Humphreys

et al.

Trends in Biochemical Sciences, Journal Year: 2023, Volume and Issue: 48(6), P. 527 - 538

Published: April 14, 2023

Language: Английский

Citations

31

Cross-linking mass spectrometry for mapping protein complex topologies in situ DOI Creative Commons
Kitaik Lee, Francis J. O’Reilly

Essays in Biochemistry, Journal Year: 2023, Volume and Issue: 67(2), P. 215 - 228

Published: Feb. 3, 2023

Cross-linking mass spectrometry has become an established technology to provide structural information on the topology and dynamics of protein complexes. Readily accessible workflows can detailed data simplified systems, such as purified However, using this study structure complexes in situ, organelles, cells, even tissues, is still a technological frontier. The complexity these systems remains considerable challenge, but there have been dramatic improvements sample handling, acquisition, processing. Here, we summarise developments describe paths towards comprehensive comparative interactomes by cross-linking spectrometry.

Language: Английский

Citations

29

New advances in cross-linking mass spectrometry toward structural systems biology DOI Open Access
Clinton Yu, Lan Huang

Current Opinion in Chemical Biology, Journal Year: 2023, Volume and Issue: 76, P. 102357 - 102357

Published: July 3, 2023

Language: Английский

Citations

25

Modeling Flexible Protein Structure With AlphaFold2 and Crosslinking Mass Spectrometry DOI Creative Commons
Karen Manalastas-Cantos, Kish R. Adoni, Matthias Pfeifer

et al.

Molecular & Cellular Proteomics, Journal Year: 2024, Volume and Issue: 23(3), P. 100724 - 100724

Published: Jan. 22, 2024

We propose a pipeline that combines AlphaFold2 (AF2) and crosslinking mass spectrometry (XL-MS) to model the structure of proteins with multiple conformations. The consists two main steps: ensemble generation using AF2 conformer selection XL-MS data. For selection, we developed scores—the monolink probability score (MP) crosslink (XLP)—both which are based on residue depth from protein surface. benchmarked MP XLP large dataset decoy structures showed our scores outperform previously scores. then tested methodology three having an open closed conformation in Protein Data Bank: Complement component 3 (C3), luciferase, glutamine-binding periplasmic protein, first generating ensembles AF2, were screened for conformations experimental In five out six cases, most accurate within ensembles—or 1 Å this model—was identified crosslinks, as assessed through score. remaining case, only monolinks (assessed score) successfully these results further improved by including "occupancy" monolinks. This serves compelling proof-of-concept effectiveness contrast, assessment was able identify cases. Our highlight complementarity methods like XL-MS, providing reliable metrics assess quality predicted models. scoring functions mentioned above available at https://gitlab.com/topf-lab/xlms-tools.

Language: Английский

Citations

14

Mapping protein–protein interactions by mass spectrometry DOI Creative Commons
Xiaonan Liu, Lawrence Abad,

Lopamudra Chatterjee

et al.

Mass Spectrometry Reviews, Journal Year: 2024, Volume and Issue: unknown

Published: May 14, 2024

Abstract Protein–protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization function of proteome, their perturbation is associated with various diseases, such as cancer, neurodegeneration, infectious diseases. Recent advances mass spectrometry (MS)‐based protein interactomics have significantly expanded our understanding PPIs cells, techniques that continue to improve terms sensitivity, specificity providing new opportunities study diverse systems. These differ depending on type interaction being studied, each approach having its set advantages, disadvantages, applicability. This review highlights recent enrichment methodologies interactomes before MS analysis compares unique features specifications. It emphasizes prospects further improvement potential applications advancing knowledge contexts.

Language: Английский

Citations

10

Nucleocapsid protein-specific monoclonal antibodies protect mice against Crimean-Congo hemorrhagic fever virus DOI Creative Commons
Aura R. Garrison, Vanessa Moresco, Xiankun Zeng

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Feb. 26, 2024

Abstract Crimean-Congo hemorrhagic fever virus (CCHFV) is a WHO priority pathogen. Antibody-based medical countermeasures offer an important strategy to mitigate severe disease caused by CCHFV. Most efforts have focused on targeting the viral glycoproteins. However, glycoproteins are poorly conserved among strains. The CCHFV nucleocapsid protein (NP) highly between Here, we investigate protective efficacy of monoclonal antibody NP. We find that anti-NP (mAb-9D5) protected female mice against lethal infection or resulted in significant delay mean time-to-death succumbed compared isotype control animals. Antibody protection independent Fc-receptor functionality and complement activity. bound NP from several strains exhibited robust cross-protection heterologous strain Afg09-2990. Our work demonstrates viable target for antibody-based therapeutics, providing another direction developing immunotherapeutics

Language: Английский

Citations

9