Detailed characterization of phosphoproteins as well as other post-translationally modified proteins is required to fully understand protein function and regulatory events in cells and organisms. Here we present a mass spectrometry (MS) based experimental strategy for the identification and mapping of phosphorylation site(s) using only low-picomole amounts of phosphoprotein starting material. Miniaturized sample preparation methods for MS facilitated localization of phosphorylation sites in phosphoproteins isolated by polyacrylamide gel electrophoresis. Custom made, nanoscale immobilized Fe(III) affinity chromatography (Fe(III)-IMAC) columns were employed for enrichment of phosphorylated peptides from crude peptide mixtures prior to off-line analysis by matrix-assisted laser desorption/ionization (MALDI) MS or nanoelectrospray tandem mass spectrometry (MS/MS). An optimized and sensitive procedure for alkaline phosphatase treatment of peptide mixtures was implemented, which in combination with nano-scale Fe(III)-IMAC and MALDI-MS allowed unambiguous identification of phosphopeptides by observation of 80 Da mass shifts. Nanoelectrospray MS/MS was used for phosphopeptide sequencing for exact determination of phosphorylation sites. The advantages and limitations of the experimental strategy was demonstrated by enrichment, identification and sequencing of phosphopeptides from the model proteins ovalbumin and bovine beta-casein isolated by gel electrophoresis. Furthermore, an autophosphorylation site at Ser-3 in recombinant human casein kinase-2 beta subunit was determined. The potential of miniaturized Fe(III)-IMAC and MALDI-MS for characterization of in vivo phosphorylated proteins was demonstrated by identification of tryptic phosphopeptides derived from the human p47/phox phosphoprotein isolated by two-dimensional gel electrophoresis.
Bradford Scholars -how to deposit your paper Overview Copyright check• Check if your publisher allows submission to a repository.• Use the Sherpa RoMEO database if you are not sure about your publisher's position or email openaccess@bradford.ac.uk.
The transitions from foraging to farming and later to pastoralism in Stone Age Eurasia (c. 11-3 thousand years before present, BP) represent some of the most dramatic lifestyle changes in human evolution. We sequenced 317 genomes of primarily Mesolithic and Neolithic individuals from across Eurasia combined with radiocarbon dates, stable isotope data, and pollen records. Genome imputation and co-analysis with previously published shotgun sequencing data resulted in >1600 complete ancient genome sequences offering fine-grained resolution into the Stone Age populations. We observe that: 1) Hunter-gatherer groups were more genetically diverse than previously known, and deeply divergent between western and eastern Eurasia. 2) We identify hitherto genetically undescribed hunter-gatherers from the Middle Don region that contributed ancestry to the later Yamnaya steppe pastoralists; 3) The genetic impact of the Neolithic transition was highly distinct, east and west of a boundary zone extending from the Black Sea to the Baltic. Large-scale shifts in genetic ancestry occurred to the west of this "Great Divide", including an almost complete replacement of hunter-gatherers in Denmark, while no substantial ancestry shifts took place during the same period to the east. This difference is also reflected in genetic relatedness within the populations, decreasing substantially in the west but not in the east where it remained high until c. 4,000 BP; 4) The second major genetic transformation around 5,000 BP happened at a much faster pace with Steppe-related ancestry reaching most parts of Europe within 1,000-years. Local Neolithic farmers admixed with incoming pastoralists in eastern, western, and southern Europe whereas Scandinavia experienced another near-complete population replacement. Similar dramatic turnover-patterns are evident in western Siberia; 5) Extensive regional differences in the ancestry components involved in these early events remain visible to this day, even within countries. Neolithic farmer ancestry is highest in southern and eastern England while Steppe-related ancestry is highest in the Celtic populations of Scotland, Wales, and Cornwall (this research has been conducted using the UK Biobank resource); 6) Shifts in diet, lifestyle and environment introduced new selection pressures involving at least 21 genomic regions. Most such variants were not universally selected across populations but were only advantageous in particular ancestral backgrounds. Contrary to previous claims, we find that selection on the FADS regions, associated with fatty acid metabolism, began before the Neolithisation of Europe. Similarly, the lactase persistence allele started increasing in frequency before the expansion of Steppe-related groups into Europe and has continued to increase up to the present. Along the genetic cline separating Mesolithic hunter-gatherers from Neolithic farmers, we find significant correlations with trait associations related to skin disorders, diet and lifestyle and mental health status, suggesting marked phenotypic differences between these groups with very different lifestyles. This work provides new insights into major transformations in recent human evolution, elucidating the complex interplay between selection and admixture that shaped patterns of genetic variation in modern populations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.