Building Spectral Libraries from Narrow-Window Data-Independent Acquisition Mass Spectrometry Data.

Advances in library-based methods for peptide detection from data-independent acquisition (DIA) mass spectrometry have made it possible to detect and quantify tens of thousands of peptides in a single mass spectrometry run. However, many of these methods rely on a comprehensive, high-quality spectral library containing information about the expected retention time and fragmentation patterns of peptides in the sample. Empirical spectral libraries are often generated through data-dependent acquisition and may suffer from biases as a result. Spectral libraries can be generated in silico, but these models are not trained to handle all possible post-translational modifications. Here, we propose a false discovery rate-controlled spectrum-centric search workflow to generate spectral libraries directly from gas-phase fractionated DIA tandem mass spectrometry data. We demonstrate that this strategy is able to detect phosphorylated peptides and can be used to generate a spectral library for accurate peptide detection and quantitation in wide-window DIA data. We compare the results of this search workflow to other library-free approaches and demonstrate that our search is competitive in terms of accuracy and sensitivity. These results demonstrate that the proposed workflow has the capacity to generate spectral libraries while avoiding the limitations of other methods.

Active medulloblastoma enhancers reveal subgroup-specific cellular origins.

Medulloblastoma is a highly malignant paediatric brain tumour, often inflicting devastating consequences on the developing child. Genomic studies have revealed four distinct molecular subgroups with divergent biology and clinical behaviour. An understanding of the regulatory circuitry governing the transcriptional landscapes of medulloblastoma subgroups, and how this relates to their respective developmental origins, is lacking. Here, using H3K27ac and BRD4 chromatin immunoprecipitation followed by sequencing (ChIP-seq) coupled with tissue-matched DNA methylation and transcriptome data, we describe the active cis-regulatory landscape across 28 primary medulloblastoma specimens. Analysis of differentially regulated enhancers and super-enhancers reinforced inter-subgroup heterogeneity and revealed novel, clinically relevant insights into medulloblastoma biology. Computational reconstruction of core regulatory circuitry identified a master set of transcription factors, validated by ChIP-seq, that is responsible for subgroup divergence, and implicates candidate cells of origin for Group 4. Our integrated analysis of enhancer elements in a large series of primary tumour samples reveals insights into cis-regulatory architecture, unrecognized dependencies, and cellular origins.

BET bromodomain proteins regulate enhancer function during adipogenesis.

Developmental transitions are guided by master regulatory transcription factors. During adipogenesis, a transcriptional cascade culminates in the expression of PPARγ and C/EBPα, which orchestrate activation of the adipocyte gene expression program. However, the coactivators controlling PPARγ and C/EBPα expression are less well characterized. Here, we show the bromodomain-containing protein, BRD4, regulates transcription of PPARγ and C/EBPα. Analysis of BRD4 chromatin occupancy reveals that induction of adipogenesis in 3T3L1 fibroblasts provokes dynamic redistribution of BRD4 to de novo super-enhancers proximal to genes controlling adipocyte differentiation. Inhibition of the bromodomain and extraterminal domain (BET) family of bromodomain-containing proteins impedes BRD4 occupancy at these de novo enhancers and disrupts transcription of Pparg and Cebpa, thereby blocking adipogenesis. Furthermore, silencing of these BRD4-occupied distal regulatory elements at the Pparg locus by CRISPRi demonstrates a critical role for these enhancers in the control of Pparg gene expression and adipogenesis in 3T3L1s. Together, these data establish BET bromodomain proteins as time- and context-dependent coactivators of the adipocyte cell state transition.

Models of human core transcriptional regulatory circuitries.

A small set of core transcription factors (TFs) dominates control of the gene expression program in embryonic stem cells and other well-studied cellular models. These core TFs collectively regulate their own gene expression, thus forming an interconnected auto-regulatory loop that can be considered the core transcriptional regulatory circuitry (CRC) for that cell type. There is limited knowledge of core TFs, and thus models of core regulatory circuitry, for most cell types. We recently discovered that genes encoding known core TFs forming CRCs are driven by super-enhancers, which provides an opportunity to systematically predict CRCs in poorly studied cell types through super-enhancer mapping. Here, we use super-enhancer maps to generate CRC models for 75 human cell and tissue types. These core circuitry models should prove valuable for further investigating cell-type-specific transcriptional regulation in healthy and diseased cells.

Tuning ß-sheet peptide self-assembly and hydrogelation behavior by modification of sequence hydrophobicity and aromaticity.

Peptide self-assembly leading to cross-ß amyloid structures is a widely studied phenomenon because of its role in amyloid pathology and the exploitation of amyloid as a functional biomaterial. The self-assembly process is governed by hydrogen bonding, hydrophobic, aromatic π-π, and electrostatic Coulombic interactions. A role for aromatic π-π interactions in peptide self-assembly leading to amyloid has been proposed, but the relative contributions of π-π versus general hydrophobic interactions in these processes are poorly understood. The Ac-(XKXK)(2)-NH(2) peptide was used to study the contributions of aromatic and hydrophobic interactions to peptide self-assembly. Position X was globally replaced by valine (Val), isoleucine (Ile), phenylalanine (Phe), pentafluorophenylalanine (F(5)-Phe), and cyclohexylalanine (Cha). At low pH, these peptides remain monomeric because of repulsion of charged lysine (Lys) residues. Increasing the solvent ionic strength to shield repulsive charge-charge interactions between protonated Lys residues facilitated cross-ß fibril formation. It was generally found that as peptide hydrophobicity increased, the required ionic strength to induce self-assembly decreased. At [NaCl] ranging from 0 to 1000 mM, the Val sequence failed to assemble. Assembly of the Phe sequence commenced at 700 mM NaCl and at 300 mM NaCl for the less hydrophobic Ile variant, even though it displayed a mixture of random coil and ß-sheet secondary structures over all NaCl concentrations. ß-Sheet formation for F(5)-Phe and Cha sequences was observed at only 20 and 60 mM NaCl, respectively. Whereas self-assembly propensity generally correlated to peptide hydrophobicity and not aromatic character the presence of aromatic amino acids imparted unique properties to fibrils derived from these peptides. Nonaromatic peptides formed fibrils of 3-15 nm in diameter, whereas aromatic peptides formed nanotape or nanoribbon architectures of 3-7 nm widths. In addition, all peptides formed fibrillar hydrogels at sufficient peptide concentrations, but nonaromatic peptides formed weak gels, whereas aromatic peptides formed rigid gels. These findings clarify the influence of aromatic amino acids on peptide self-assembly processes and illuminate design principles for the inclusion of aromatic amino acids in amyloid-derived biomaterials.

Highly Parallel Quantification and Compartment Localization of Transcription Factors and Nuclear Proteins.

Transcription factors and other chromatin-associated proteins are difficult to quantify comprehensively. Here, we combine facile nuclear sub-fractionation with data-independent acquisition mass spectrometry to achieve rapid, sensitive, and highly parallel quantification of the nuclear proteome in human cells. We apply this approach to quantify the response to acute degradation of BET bromodomains, revealing unexpected chromatin regulatory dynamics. The method is simple and enables system-level study of previously inaccessible chromatin and genome regulators.

Targeting nuclear receptor NR4A1-dependent adipocyte progenitor quiescence promotes metabolic adaptation to obesity.

Adipocyte turnover in adulthood is low, suggesting that the cellular source of new adipocytes, the adipocyte progenitor (AP), resides in a state of relative quiescence. Yet the core transcriptional regulatory circuitry (CRC) responsible for establishing a quiescent state and the physiological significance of AP quiescence are incompletely understood. Here, we integrate transcriptomic data with maps of accessible chromatin in primary APs, implicating the orphan nuclear receptor NR4A1 in AP cell-state regulation. NR4A1 gain and loss of function in APs ex vivo decreased and enhanced adipogenesis, respectively. Adipose tissue of Nr4a1-/- mice demonstrated higher proliferative and adipogenic capacity compared with that of WT mice. Transplantation of Nr4a1-/- APs into the subcutaneous adipose tissue of WT obese recipients improved metrics of glucose homeostasis relative to administration of WT APs. Collectively, these data identify NR4A1 as a previously unrecognized constitutive regulator of AP quiescence and suggest that augmentation of adipose tissue plasticity may attenuate negative metabolic sequelae of obesity.

Enhancer Architecture and Essential Core Regulatory Circuitry of Chronic Lymphocytic Leukemia.

Enhancer profiling is a powerful approach for discovering cis-regulatory elements that define the core transcriptional regulatory circuits of normal and malignant cells. Gene control through enhancer activity is often dominated by a subset of lineage-specific transcription factors. By integrating measures of chromatin accessibility and enrichment for H3K27 acetylation, we have generated regulatory landscapes of chronic lymphocytic leukemia (CLL) samples and representative cell lines. With super enhancer-based modeling of regulatory circuits and assessments of transcription factor dependencies, we discover that the essential super enhancer factor PAX5 dominates CLL regulatory nodes and is essential for CLL cell survival. Targeting enhancer signaling via BET bromodomain inhibition disrupts super enhancer-dependent gene expression with selective effects on CLL core regulatory circuitry, conferring potent anti-tumor activity.

Structure-guided DOT1L probe optimization by label-free ligand displacement.

The DOT1L lysine methyltransferase has emerged as a validated therapeutic target in MLL-rearranged (MLLr) acute leukemias. Although S-adenosylmethionine competitive inhibitors have demonstrated pharmacological proof-of-principle in MLLr-leukemia, these compounds require further optimization to improve cellular potency and pharmacokinetic stability. Limiting DOT1L inhibitor discovery and ligand optimization have been complex biochemical methods often using radionucleotides and cellular methods requiring prolonged culture. We therefore developed a new suite of assay technologies that allows comparative assessment of chemical tools for DOT1L in a miniaturized format. Coupling these assays with structural information, we developed new insights into DOT1L ligand binding and identified several functionalized probes with increased cellular potency (IC50 values ∼10 nM) and excellent selectivity for DOT1L. Together these assay technologies define a platform capability for discovery and optimization of small-molecule DOT1L inhibitors.

The use of small molecules in somatic-cell reprogramming.

Pioneering work over the past years has highlighted the remarkable ability of manipulating cell states through exogenous, mostly transcription factor-induced reprogramming. The use of small molecules and reprogramming by transcription factors share a common history starting with the early AZA and MyoD experiments in fibroblast cells. Recent work shows that a combination of small molecules can replace all of the reprogramming factors and many previous studies have demonstrated their use in enhancing efficiencies or replacing individual factors. Here we provide a brief introduction to reprogramming followed by a detailed review of the major classes of small molecules that have been used to date and what future opportunities can be expected from these.