| 2. |
- Echelmeier, A., et al.
(author)
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Segmented flow generator for serial crystallography at the European X-ray free electron laser
- 2020
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In: Nature Communications. - : Nature Research. - 2041-1723. ; 11:1
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Journal article (peer-reviewed)abstract
- Serial femtosecond crystallography (SFX) with X-ray free electron lasers (XFELs) allows structure determination of membrane proteins and time-resolved crystallography. Common liquid sample delivery continuously jets the protein crystal suspension into the path of the XFEL, wasting a vast amount of sample due to the pulsed nature of all current XFEL sources. The European XFEL (EuXFEL) delivers femtosecond (fs) X-ray pulses in trains spaced 100 ms apart whereas pulses within trains are currently separated by 889 ns. Therefore, continuous sample delivery via fast jets wastes >99% of sample. Here, we introduce a microfluidic device delivering crystal laden droplets segmented with an immiscible oil reducing sample waste and demonstrate droplet injection at the EuXFEL compatible with high pressure liquid delivery of an SFX experiment. While achieving ~60% reduction in sample waste, we determine the structure of the enzyme 3-deoxy-D-manno-octulosonate-8-phosphate synthase from microcrystals delivered in droplets revealing distinct structural features not previously reported.
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| 5. |
- Vazquez, SE, et al.
(author)
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Autoantibody discovery across monogenic, acquired, and COVID19-associated autoimmunity with scalable PhIP-Seq
- 2022
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In: bioRxiv : the preprint server for biology. - : Cold Spring Harbor Laboratory.
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Journal article (other academic/artistic)abstract
- Phage Immunoprecipitation-Sequencing (PhIP-Seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-Seq for autoantigen discovery, including our previous work (Vazquez et al. 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki Disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), and finally, mild and severe forms of COVID19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as PDYN in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in 2 patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-Seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID19, including the endosomal protein EEA1. Together, scaled PhIP-Seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.
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