Evidence map›Paper›PMID 40448450›Full record

ArticleBiophysical journal2025

Single-particle tracking of genetically encoded nanoparticles: Optimizing expression for cytoplasmic diffusion studies.

Elizaveta Korunova, Vitali Sikirzhytski, Jeffery L Twiss, Paula Vasquez, Michael Shtutman

Abstract read
In one paragraph

Article in Biophysical journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Elizaveta KorunovaDepartment of Drug Discovery & Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina.
Vitali SikirzhytskiDepartment of Drug Discovery & Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina.
Jeffery L TwissDepartment of Biological Sciences, College of Arts and Sciences, University of South Carolina, Columbia, South Carolina.
Paula VasquezDepartment of Mathematics, College of Arts and Sciences, University of South Carolina, Columbia, South Carolina. Electronic address: paula@math.sc.edu.
Michael ShtutmanDepartment of Drug Discovery & Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina. Electronic address: shtutmanm@cop.sc.edu.

Funding

Microscopy and Flow Cytometry CoreP30GM154632 · NIGMS · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI Hippokratis Kiaris · 2024 to 2026
$4.5M
Knowledge discovery and machine learning to elucidate the mechanisms of HIV activity and interaction with substance use disorderR01DA054992 · NIDA · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI SAFRO, ILYA, SHTUTMAN, MICHAEL · 2021 to 2025
$2.1M
Targeting Immunometabolism: a novel role for itaconate in the treatment of HIV-associated neurocognitive disorder and cocaine use disorderR21DA058586 · NIDA · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI BOOZE, ROSEMARIE M, FRIZZELL, NORMA · 2023 to 2024
$401k
NIDA NIH HHS R01 DA054992NIDA NIH HHS R21 DA058586NIGMS NIH HHS P30 GM154632
6 · The paper itself

Abstract

Single-particle tracking (SPT) is a powerful technique for probing the diverse physical properties of the cytoplasm. Genetically encoded nanoparticles provide an especially convenient tool for such investigations, as they can be expressed and tracked in cells via fluorescence. Among these, 40-nm genetically encoded multimerics (GEMs) provide a unique opportunity to explore the cytoplasm. Their size corresponds to that of ribosomes and big protein complexes, allowing us to investigate the effects of the cytoplasm on the diffusivity of these objects while excluding the influence of chemical interactions during stressful events and pathological conditions. However, the effects of GEM expression levels on the measured cytoplasmic diffusivity remain largely uncharacterized in mammalian cells. To optimize the GEMs tracking and assess expression level effects, we developed a doxycycline-inducible GEM expression system and compared it with a previously reported constitutive expression system. The inducible GEM expression system reduced the number of GEM particles from 2000 to as low as 5-500 per average 2D cell cytoplasmic area, depending on doxycycline concentration and incubation time. This optimization enabled adjustment of particle density for imaging and improved homogeneity across the cell population. Moreover, we enhanced the analysis of GEM diffusivity by incorporating an effective diffusion coefficient that accounts for the type of motion and by quantifying motion heterogeneity through standard deviations of particle displacements within and between cells.

Indexed as

CytoplasmNanoparticlesSingle Molecule ImagingDiffusionDoxycyclineGene ExpressionHumansDoxycycline

Identifiers

PMID40448450
PMCPMC12256916

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.