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Lin, C.-W.

Publications and source records attributed to Lin, C.-W..

22 records · Page 2Linked to original sources

Recapitulating the frataxin activation mechanism in an engineered bacterial cysteine desulfurase supports the architectural switch model

Iron-sulfur (Fe-S) clusters have a key role in many biochemical processes and are essential for most life forms. Despite recent mechanistic advances in understanding the Fe-S cluster biosynthetic pathway, critical questions remain unresolved. Although human NFS1 and E. coli IscS share [~]60% sequence identity, NFS1 exhibits low activity and requires activation by the Friedreichs ataxia protein frataxin (FXN) for in vivo function. Surprisingly, structures of the human complex reveal three distinct quaternary structures with one form exhibiting the same subunit interactions as IscS. An architectural switch model has been proposed in which evolutionarily lost interactions between NFS1 subunits results in the formation of low-activity architectures; FXN binding compensates for these lost interactions and facilitates a subunit rearrangement to activate the complex. Here, we used a structure and evolution-guided approach to identify three conserved residues proposed to weaken interactions between NFS1 subunits and transplanted these amino acids into IscS. Compared to native IscS, the engineered variant had a 4000-fold weaker dimer interface and diminished activity that correlated with the absence of the second catalytic subunit. Remarkably, the addition of the FXN homolog to the engineered variant stimulated the decay of the Cys-quinonoid pyridoxal 5-phosphate intermediate, shifted IscS from the monomeric to dimeric form, and increased the cysteine desulfurase activity, reproducing results from the human system and supporting the architectural switch model. Overall, these studies indicate a weakening of the homodimeric interface was a key development during the evolution of the eukaryotic system and provide new insights into the role of FXN.

biochemistry↗

High Spatial Resolution Ambient Ionization Mass Spectrometry Imaging Using Microscopy Image Fusion

Mass spectrometry imaging (MSI) using ambient ionization technique enables a direct chemical investigation of biological samples with minimal sample pretreatment. However, detailed morphological information of the sample is often lost due to its limited spatial resolution. In this study, predictive high-resolution molecular imaging was produced by the fusion of ambient ionization MSI with optical microscopy of routine hematoxylin and eosin (H&E) staining produces. Specifically, desorption electrospray ionization (DESI) and nanospray desorption electrospray ionization (nanoDESI) mass spectrometry are employed to visualize lipid and protein species on mice tissue sections. The resulting molecular distributions obtained by ambient ionization MSI-microscopy fusion are verified with matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) MSI and immunohistochemistry (IHC) staining. Label-free molecular imaging with 5-m spatial resolution can be acquired using DESI and nanoDESI, whereas the typical spatial resolution of ambient ionization MSI is ~100 m. In this regard, sharpened molecular histology of tissue sections is achieved, providing complementary references to the pathology. Such a multimodality integration enables the discovery of potential tumor biomarkers. After image fusion, more than a dozen of potential biomarkers that could be used to determine the tumor margins on a metastatic mouse lung tissue section and Luminal B breast tumor tissue section are identified.

bioinformatics↗

Sterol-O acyltransferase 1 is inhibited by gga-miR-181a-5p and gga-miR-429-3p through the TGFβ pathway in endodermal epithelial cells of Japanese quail

Nutrients are utilized and re-constructed by endodermal epithelial cells (EECs) in yolk sac membranes in avian species. Sterol-O acyltransferase 1 (SOAT1) is the key enzyme to convert cholesterol to cholesteryl ester for delivery to growing embryos. During development, absorption of yolk is matched with significant changes of SOAT1 mRNA and enzyme activity. miRNAs regulate angiogenesis and metabolism during mammalian development. However, the involvement of miRNAs in lipid utilization during avian embryogenesis remains ambiguous.\n\nUsing a miRNA sequencing technique, we found several candidate miRNAs and confirmed expression patterns with real time PCR. They were selected for as candidates targeting the receptor (TGF{beta} receptor type 1, TGFBR1) that may regulate SOAT1. Similar to SOAT1 mRNA accumulation, the gga-miR-181a-5p expression was gradually elevated during development, but the concentration of gga-miR-429-3p was in the opposite direction. Transfection with gga-miR-181a-5p or gga-miR-429-3p inhibited TGFBR1 and SOAT1 in EECs. The 3 untranslated region (3UTR) of TGFBR1 was then confirmed to be one of the targets of gga-miR-181a-5p and gga-miR-429-3p. Taken together, expression of miRNAs during embryonic development regulates SOAT1 expression by inhibiting the 3UTR of TGFBR1. This is indicative of possible regulation of avian yolk lipid utilization and modification of hatchability by changing miRNA expressions.

molecular biology↗

Comparative Pathway Integrator: a framework of meta-analytic integration of multiple transcriptomic studies for consensual and differential pathway analysis

MotivationPathway analysis provides a knowledge-driven approach to interpret differentially expressed genes associated with disease status. Many tools have been developed to analyze a single study. When multiple studies of different conditions are jointly analyzed, novel integrative tools are needed. In addition, pathway redundancy issue introduced by combining public pathway databases hinders knowledge discovery.\n\nMethods and ResultsWe present a meta-analytic integration tool, Comparative Pathway Integrator (CPI), to address these issues using adaptively weighted Fishers method to discover consensual and differential enrichment patterns, consensus clustering to reduce pathway redundancy, and a novel text mining algorithm to assist interpretation of the pathway clusters. We applied CPI to jointly analyze six psychiatric disorder transcriptomic studies to demonstrate its effectiveness, and found functions confirmed by previous biological studies as well novel enrichment patterns.\n\nAvailabilityCPI is accessible online: http://tsenglab.biostat.pitt.edu/software.htm.\n\nContactxiangruz@andrew.cmu.edu

bioinformatics↗