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    Announcements

    Northwestern Team Develops System for Simplifying Sample Cleanup in Top-Down Proteomics

    The lab of Northwestern University researcher Neil Kelleher has developed an on-line system for clean up of top-down proteomics samples following gel eluted liquid fraction entrapment electrophoresis (GELFrEE) fractionation.The system, detailed in a paper published in May 2015 in the Journal of Proteome Research, uses asymmetrical flow field-flow fractionation (AF4) to address what is a key challenge in top-down proteomic workflows, and could make top-down approaches more widely shareable as well as improve their applicability to clinical work, Philip Compton, director of instrumentation at NorthWestern's Proteomics Center of Excellence and an author on the paper, told GenomeWeb.

    Kelleher Lab featured in Feinberg News Center

    Chemicals found in nature have long been known for their potential to benefit human health, directly and indirectly forming the basis for antibiotics, anti-cancer therapies and other drugs. But identifying promising bioactive compounds within vast natural resources is like slowly chipping away at a mountain range in search of gold.In a recent study published in Nature Chemical Biology, Northwestern Medicine scientists developed a method to systematically explore large data sets of bacterial molecules to identify thousands of potential drug leads in one fell swoop.

    Hear about the Top Down version of the Human Proteome Project!

    The tectonic collision of biology with separation science, MS, and informatics occurred over the past 15 years and was driven by contributions from more than 100 laboratories. Like budding yeast, MS is sprouting emergent approaches for the direct profiling and MS/MS analysis of heterogeneous proteins in ever more complex mixtures. Such approaches promise to determine molecular indicators of complex diseases and deepen our understanding of dynamic regulatory mechanisms in cell biology.

    Kelleher lab awarded $1M from Keck Foundation

    Congratulations to Neil Kelleher for being awarded a $1 million grant from the Keck Foundation. This grant will be used to develop a hybrid mass spectrometer. Philip Compton, John Tran, and Adam Catherman will also be involved in the project. To read more about the project and the Keck Foundation, please see an article published on the Northwestern University website.

    About the Kelleher Group

    Chromatin Oncobiology

    Our Chromatin Oncobiology and DNA-Damage subgroup continues to dig deeper into the "histone code", a complex mixture of post-translational modifications that together determine a host of cellular processes. We are interested in visualizing dynamic histone PTM changes simultaneously on multiple sites. Through application of technology developed in our Top Down Proteomics subgroup, we are able to apply "Precision Proteomics" to histone analysis.

    Computational Proteomics

    Our Computational Proteomics subgroup focuses on the development of specialized software for the analysis of intact proteins and peptides. Learn more about ProSight PTM 2.0, our in house designed analysis tool, on this site.

    Natural Products Discovery

    Our Natural Products subgroup is focused on the discovery and biosynthesis of novel natural products. Developments from this subgroup include the introduction of the PrISM platform, geared towards the identification of natural products synthesized by nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs) without prior knowledge of a gene sequence. This is made possible by our ability to detect a phosphopantetheinyl (Ppant) ejection marker ion for NRPS/PKS thiolation domains. We also work in collaboration with groups from other universities to provide mass spectrometry analysis of novel biochemical systems.

    Top Down Proteomics

    The main focus for our Top Down Proteomics subgroup is to push the limits for whole proteome analysis of mammalian cells, striving for a future in which Top Down analysis rivals that of Bottom Up in the number of protein identifications per run. Recently we have seen progress towards this very goal with the introduction of a separation platform specifically designed to minimize the most common problem in Top Down Proteomics, intact protein separations. This platform effectively reduces sample complexity and separates proteins depending on size, resulting in an opportunity for the researcher to select the optimal analysis method for the sample.

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