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1.
Bio Protoc ; 12(4): e4322, 2022 Feb 20.
Article in English | MEDLINE | ID: mdl-35340291

ABSTRACT

Malaria remains a major public health issue, infecting nearly 220 million people every year. The spread of drug-resistant strains of Plasmodium falciparum around the world threatens the progress made against this disease. Therefore, identifying druggable and essential pathways in P. falciparum parasites remains a major area of research. One poorly understood area of parasite biology is the formation of disulfide bonds, which is an essential requirement for the folding of numerous proteins. Specialized chaperones with thioredoxin (Trx) domains catalyze the redox functions necessary for breaking incorrect and forming correct disulfide bonds in proteins. Defining the substrates of these redox chaperones is difficult and immunoprecipitation based assays cannot distinguish between substrates and interacting partners. Further, the substrate or client interactions with the redox chaperones are usually transient in nature. Activity based crosslinkers that rely on the nucleophilic cysteines on Trx domains and the disulfide bond forming cysteines on clients provide an easily scalable method to trap and identify the substrates of Trx-domain containing chaperones. The cell permeable crosslinker divinyl sulfone (DVSF) is active only in the presence of nucleophilic cysteines in proteins and, therefore, traps Trx domains with their substrates, as they form mixed disulfide bonds during the course of their catalytic activity. This allows the identification of substrates that rely on Trx activity for their folding, as well as discovering small molecules that interfere with Trx domain activity. Graphic abstract: Identification of thioredoxin domain substrates via divinylsulfone crosslinking and immunoprecipitation-mass spectrometry.

2.
Article in English | MEDLINE | ID: mdl-33139288

ABSTRACT

A2059G mutation in the 23S rRNA gene is the only reported mechanism conferring high-level azithromycin resistance (HL-AZMR) in Neisseria gonorrhoeae Through U.S. gonococcal antimicrobial resistance surveillance projects, we identified four HL-AZMR gonococcal isolates lacking this mutational genotype. Genetic analysis revealed an A2058G mutation of 23S rRNA alleles in all four isolates. In vitro selected gonococcal strains with homozygous A2058G recapitulated the HL-AZMR phenotype. Taken together, we postulate that the A2058G mutation confers HL-AZMR in N. gonorrhoeae.


Subject(s)
Azithromycin , Gonorrhea , Anti-Bacterial Agents/pharmacology , Azithromycin/pharmacology , Drug Resistance, Bacterial/genetics , Gonorrhea/drug therapy , Humans , Microbial Sensitivity Tests , Mutation , Neisseria gonorrhoeae/genetics , RNA, Ribosomal, 23S/genetics
3.
Matter ; 3(4): 1087-1113, 2020 Oct 07.
Article in English | MEDLINE | ID: mdl-33103115

ABSTRACT

The success of in vivo neural interfaces relies on their long-term stability and large scale in interrogating and manipulating neural activity after implantation. Conventional neural probes, owing to their limited spatiotemporal resolution and scale, face challenges for studying the massive, interconnected neural network in its native state. In this review, we argue that taking inspiration from biology will unlock the next generation of in vivo bioelectronic neural interfaces. Reducing the feature sizes of bioelectronic neural interfaces to mimic those of neurons enables high spatial resolution and multiplexity. Additionally, chronic stability at the device-tissue interface is realized by matching the mechanical properties of bioelectronic neural interfaces to those of the endogenous tissue. Further, modeling the design of neural interfaces after the endogenous topology of the neural circuitry enables new insights into the connectivity and dynamics of the brain. Lastly, functionalization of neural probe surfaces with coatings inspired by biology leads to enhanced tissue acceptance over extended timescales. Bioinspired neural interfaces will facilitate future developments in neuroscience studies and neurological treatments by leveraging bidirectional information transfer and integrating neuromorphic computing elements.

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