An autoinhibitory switch of the LSD1 disordered region controls enhancer silencing.

Transcriptional coregulators and transcription factors (TFs) contain intrinsically disordered regions (IDRs) that are critical for their association and function in gene regulation. More recently, IDRs have been shown to promote multivalent protein-protein interactions between coregulators and TFs to drive their association into condensates. By contrast, here we demonstrate how the IDR of the corepressor LSD1 excludes TF association, acting as a dynamic conformational switch that tunes repression of active cis-regulatory elements. Hydrogen-deuterium exchange shows that the LSD1 IDR interconverts between transient open and closed conformational states, the latter of which inhibits partitioning of the protein's structured domains with TF condensates. This autoinhibitory switch controls leukemic differentiation by modulating repression of active cis-regulatory elements bound by LSD1 and master hematopoietic TFs. Together, these studies unveil alternative mechanisms by which disordered regions and their dynamic crosstalk with structured regions can shape coregulator-TF interactions to control cis-regulatory landscapes and cell fate.

High-Efficiency Enrichment by Saturating Nanoliters of Protein Affinity Media.

Affinity-purification mass spectrometry (AP-MS) is an established technique for identifying protein-protein interactions (PPIs). The basic technology involves immobilizing a high-specificity ligand to a solid-phase support (e.g., an agarose or magnetic bead) to pull down protein(s) of interest from cell lysates. Although these supports are engineered to minimize interactions with background protein, the conventional method recovers mostly nonspecific binders. The law of mass action for dilute solutions has taught us to use an excess of beads to capture all target proteins, especially weakly interacting ones. However, modern microbead technology presents a binding environment that is much different from a dilute solution. We describe a fluidic platform that captures and processes ultralow nanoliter quantities of magnetic particles, simultaneously increasing the efficiency of PPI detection and strongly suppressing nonspecific binding. We demonstrate the concept with synthetic mixtures of tagged protein and illustrate performance with a variety of AP-MS experiment types. These include a BioID experiment targeting lamin-A interactors from HeLa cells and pulldowns using GFP-tagged proteins associated with a double-strand DNA repair mechanism. We show that efficient extraction requires saturation of the solid-phase support and that <10 nL of beads is sufficient to generate comprehensive protein interaction maps.

Improving Spectral Validation Rates in Hydrogen-Deuterium Exchange Data Analysis.

The data analysis practices associated with hydrogen-deuterium exchange mass spectrometry (HX-MS) lag far behind that of most other MS-based protein analysis tools. A reliance on external tools from other fields and a persistent need for manual data validation restrict this powerful technology to the expert user. Here, we provide an extensive upgrade to the HX data analysis suite available in the Mass Spec Studio in the form of two new apps (HX-PIPE and HX-DEAL), completing a workflow that provides an HX-tailored peptide identification capability, accelerated validation routines, automated spectral deconvolution strategies, and a rich set of exportable graphics and statistical reports. With these new tools, we demonstrate that the peptide identifications obtained from undeuterated samples generated at the start of a project contain information that helps predict and control the extent of manual validation required. We also uncover a large fraction of HX-usable peptides that remains unidentified in most experiments. We show that automated spectral deconvolution routines can identify exchange regimes in a project-wide manner, although they remain difficult to accurately assign in all scenarios. Taken together, these new tools provide a robust and complete solution suitable for the analysis of high-complexity HX-MS data.

Lactoferrin binding protein B - a bi-functional bacterial receptor protein.

Lactoferrin binding protein B (LbpB) is a bi-lobed outer membrane-bound lipoprotein that comprises part of the lactoferrin (Lf) receptor complex in Neisseria meningitidis and other Gram-negative pathogens. Recent studies have demonstrated that LbpB plays a role in protecting the bacteria from cationic antimicrobial peptides due to large regions rich in anionic residues in the C-terminal lobe. Relative to its homolog, transferrin-binding protein B (TbpB), there currently is little evidence for its role in iron acquisition and relatively little structural and biophysical information on its interaction with Lf. In this study, a combination of crosslinking and deuterium exchange coupled to mass spectrometry, information-driven computational docking, bio-layer interferometry, and site-directed mutagenesis was used to probe LbpB:hLf complexes. The formation of a 1:1 complex of iron-loaded Lf and LbpB involves an interaction between the Lf C-lobe and LbpB N-lobe, comparable to TbpB, consistent with a potential role in iron acquisition. The Lf N-lobe is also capable of binding to negatively charged regions of the LbpB C-lobe and possibly other sites such that a variety of higher order complexes are formed. Our results are consistent with LbpB serving dual roles focused primarily on iron acquisition when exposed to limited levels of iron-loaded Lf on the mucosal surface and effectively binding apo Lf when exposed to high levels at sites of inflammation.

Loss of Kmt2c or Kmt2d drives brain metastasis via KDM6A-dependent upregulation of MMP3.

KMT2C and KMT2D, encoding histone H3 lysine 4 methyltransferases, are among the most commonly mutated genes in triple-negative breast cancer (TNBC). However, how these mutations may shape epigenomic and transcriptomic landscapes to promote tumorigenesis is largely unknown. Here we describe that deletion of Kmt2c or Kmt2d in non-metastatic murine models of TNBC drives metastasis, especially to the brain. Global chromatin profiling and chromatin immunoprecipitation followed by sequencing revealed altered H3K4me1, H3K27ac and H3K27me3 chromatin marks in knockout cells and demonstrated enhanced binding of the H3K27me3 lysine demethylase KDM6A, which significantly correlated with gene expression. We identified Mmp3 as being commonly upregulated via epigenetic mechanisms in both knockout models. Consistent with these findings, samples from patients with KMT2C-mutant TNBC have higher MMP3 levels. Downregulation or pharmacological inhibition of KDM6A diminished Mmp3 upregulation induced by the loss of histone-lysine N-methyltransferase 2 (KMT2) and prevented brain metastasis similar to direct downregulation of Mmp3. Taken together, we identified the KDM6A-matrix metalloproteinase 3 axis as a key mediator of KMT2C/D loss-driven metastasis in TNBC.

Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology.

We present a hydrogen/deuterium exchange workflow coupled to tandem mass spectrometry (HX-MS2) that supports the acquisition of peptide fragment ions alongside their peptide precursors. The approach enables true auto-curation of HX data by mining a rich set of deuterated fragments, generated by collisional-induced dissociation (CID), to simultaneously confirm the peptide ID and authenticate MS1-based deuteration calculations. The high redundancy provided by the fragments supports a confidence assessment of deuterium calculations using a combinatorial strategy. The approach requires data-independent acquisition (DIA) methods that are available on most MS platforms, making the switch to HX-MS2 straightforward. Importantly, we find that HX-DIA enables a proteomics-grade approach and wide-spread applications. Considerable time is saved through auto-curation and complex samples can now be characterized and at higher throughput. We illustrate these advantages in a drug binding analysis of the ultra-large protein kinase DNA-PKcs, isolated directly from mammalian cells.

Harmonizing structural mass spectrometry analyses in the mass spec studio.

Structural Mass Spectrometry (SMS) provides a comprehensive toolbox for the analysis of protein structure and function. It offers multiple sources of structural information that are increasingly useful for integrative structural modeling of complex protein systems. As MS-based structural workflows scale to larger systems, consistent and coherent data interpretation resources are needed to better support modeling. Unlike the proteomics community, practitioners of SMS lack adequate computational tools. Here, we review new developments in the Mass Spec Studio: an expandable ecosystem of workflows for the analysis of complementary SMS techniques with linkages to modeling. Current functionality in the Studio (version 2) supports three major SMS workflows (crosslinking, hydrogen/deuterium exchange and covalent labelling) and two pipelines for structural modeling, with a special focus on data integration. The Mass Spec Studio is an architecture focused on rapid and robust extension of functionality by a community of developers. SIGNIFICANCE: This review surveys the new data analysis capabilities within the Mass Spec Studio, a rich framework for rapid software development specifically targeting the community of structural proteomics and structural mass spectrometry. Updates to crosslinking, hydrogen/deuterium-exchange and covalent labeling apps are provided as well as a utility for translating such analyses into restraints that support integrative structural modeling. These new capabilities, together with the underlying design tools and content, provide the community with a wealth of resources to tackle complex structural problem and design new approaches to data analysis.

A substrate binding model for the KEOPS tRNA modifying complex.

The KEOPS complex, which is conserved across archaea and eukaryotes, is composed of four core subunits; Pcc1, Kae1, Bud32 and Cgi121. KEOPS is crucial for the fitness of all organisms examined. In humans, pathogenic mutations in KEOPS genes lead to Galloway-Mowat syndrome, an autosomal-recessive disease causing childhood lethality. Kae1 catalyzes the universal and essential tRNA modification N6-threonylcarbamoyl adenosine, but the precise roles of all other KEOPS subunits remain an enigma. Here we show using structure-guided studies that Cgi121 recruits tRNA to KEOPS by binding to its 3' CCA tail. A composite model of KEOPS bound to tRNA reveals that all KEOPS subunits form an extended tRNA-binding surface that we have validated in vitro and in vivo to mediate the interaction with the tRNA substrate and its modification. These findings provide a framework for understanding the inner workings of KEOPS and delineate why all KEOPS subunits are essential.