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1.
Curr Biol ; 32(17): 3862-3870.e6, 2022 09 12.
Article in English | MEDLINE | ID: mdl-35961316

ABSTRACT

Intracellular transport is essential for neuronal function and survival. The most effective plus-end-directed neuronal transporter is the kinesin-3 KIF1C, which transports large secretory vesicles and endosomes.1-4 Mutations in KIF1C cause hereditary spastic paraplegia and cerebellar dysfunction in human patients.5-8 In contrast to other kinesin-3s, KIF1C is a stable dimer and a highly processive motor in its native state.9,10 Here, we establish a baseline for the single-molecule mechanics of Kif1C. We show that full-length KIF1C molecules can processively step against the load of an optical trap and reach average stall forces of 3.7 pN. Compared with kinesin-1, KIF1C has a higher propensity to slip backward under load, which results in a lower maximal single-molecule force. However, KIF1C remains attached to the microtubule while slipping backward and re-engages quickly, consistent with its super processivity. Two pathogenic mutations, P176L and R169W, that cause hereditary spastic paraplegia in humans7,8 maintain fast, processive single-molecule motility in vitro but with decreased run length and slightly increased unloaded velocity compared with the wild-type motor. Under load in an optical trap, force generation by these mutants is severely reduced. In cells, the same mutants are impaired in producing sufficient force to efficiently relocate organelles. Our results show how its mechanics supports KIF1C's role as an intracellular transporter and explain how pathogenic mutations at the microtubule-binding interface of KIF1C impair the cellular function of these long-distance transporters and result in neuronal disease.


Subject(s)
Kinesins , Spastic Paraplegia, Hereditary , Humans , Kinesins/genetics , Microtubules/metabolism , Mutation , Protein Binding , Spastic Paraplegia, Hereditary/genetics , Spastic Paraplegia, Hereditary/metabolism
2.
ACS Sens ; 6(10): 3696-3705, 2021 10 22.
Article in English | MEDLINE | ID: mdl-34634204

ABSTRACT

The COVID-19 pandemic, and future pandemics, require diagnostic tools to track disease spread and guide the isolation of (a)symptomatic individuals. Lateral-flow diagnostics (LFDs) are rapid and of lower cost than molecular (genetic) tests, with current LFDs using antibodies as their recognition units. Herein, we develop a prototype flow-through device (related, but distinct to LFDs), utilizing N-acetyl neuraminic acid-functionalized, polymer-coated, gold nanoparticles as the detection/capture unit for SARS-COV-2, by targeting the sialic acid-binding site of the spike protein. The prototype device can give rapid results, with higher viral loads being faster than lower viral loads. The prototype's effectiveness is demonstrated using spike protein, lentiviral models, and a panel of heat-inactivated primary patient nasal swabs. The device was also shown to retain detection capability toward recombinant spike proteins from several variants (mutants) of concern. This study provides the proof of principle that glyco-lateral-flow devices could be developed to be used in the tracking monitoring of infectious agents, to complement, or as alternatives to antibody-based systems.


Subject(s)
COVID-19 , Metal Nanoparticles , Gold , Humans , Pandemics , Polysaccharides , SARS-CoV-2
3.
ACS Cent Sci ; 6(11): 2046-2052, 2020 Nov 25.
Article in English | MEDLINE | ID: mdl-33269329

ABSTRACT

There is an urgent need to understand the behavior of the novel coronavirus (SARS-COV-2), which is the causative agent of COVID-19, and to develop point-of-care diagnostics. Here, a glyconanoparticle platform is used to discover that N-acetyl neuraminic acid has affinity toward the SARS-COV-2 spike glycoprotein, demonstrating its glycan-binding function. Optimization of the particle size and coating enabled detection of the spike glycoprotein in lateral flow and showed selectivity over the SARS-COV-1 spike protein. Using a virus-like particle and a pseudotyped lentivirus model, paper-based lateral flow detection was demonstrated in under 30 min, showing the potential of this system as a low-cost detection platform.

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