BRCA1/BARD1 intrinsically disordered regions facilitate chromatin recruitment and ubiquitylation.

BRCA1/BARD1 is a tumor suppressor E3 ubiquitin (Ub) ligase with roles in DNA damage repair and in transcriptional regulation. BRCA1/BARD1 RING domains interact with nucleosomes to facilitate mono-ubiquitylation of distinct residues on the C-terminal tail of histone H2A. These enzymatic domains constitute a small fraction of the heterodimer, raising the possibility of functional chromatin interactions involving other regions such as the BARD1 C-terminal domains that bind nucleosomes containing the DNA damage signal H2A K15-Ub and H4 K20me0, or portions of the expansive intrinsically disordered regions found in both subunits. Herein, we reveal novel interactions that support robust H2A ubiquitylation activity mediated through a high-affinity, intrinsically disordered DNA-binding region of BARD1. These interactions support BRCA1/BARD1 recruitment to chromatin and sites of DNA damage in cells and contribute to their survival. We also reveal distinct BRCA1/BARD1 complexes that depend on the presence of H2A K15-Ub, including a complex where a single BARD1 subunit spans adjacent nucleosome units. Our findings identify an extensive network of multivalent BARD1-nucleosome interactions that serve as a platform for BRCA1/BARD1-associated functions on chromatin.

Data-Independent Acquisition Protease-Multiplexing Enables Increased Proteome Sequence Coverage Across Multiple Fragmentation Modes.

The use of multiple proteases has been shown to increase protein sequence coverage in proteomics experiments; however, due to the additional analysis time required, it has not been widely adopted in routine data-dependent acquisition (DDA) proteomic workflows. Alternatively, data-independent acquisition (DIA) has the potential to analyze multiplexed samples from different protease digests, but has been primarily optimized for fragmenting tryptic peptides. Here we evaluate a DIA multiplexing approach that combines three proteolytic digests (Trypsin, AspN, and GluC) into a single sample. We first optimize data acquisition conditions for each protease individually with both the canonical DIA fragmentation mode (beam type CID), as well as resonance excitation CID, to determine optimal consensus conditions across proteases. Next, we demonstrate that application of these conditions to a protease-multiplexed sample of human peptides results in similar protein identifications and quantitative performance as compared to trypsin alone, but enables up to a 63% increase in peptide detections, and a 45% increase in nonredundant amino acid detections. Nontryptic peptides enabled noncanonical protein isoform determination and resulted in 100% sequence coverage for numerous proteins, suggesting the utility of this approach in applications where sequence coverage is critical, such as protein isoform analysis.

CIDer: A Statistical Framework for Interpreting Differences in CID and HCD Fragmentation.

Library searching is a powerful technique for detecting peptides using either data independent or data dependent acquisition. While both large-scale spectrum library curators and deep learning prediction approaches have focused on beam-type CID fragmentation (HCD), resonance CID fragmentation remains a popular technique. Here we demonstrate an approach to model the differences between HCD and CID spectra, and present a software tool, CIDer, for converting libraries between the two fragmentation methods. We demonstrate that just using a combination of simple linear models and basic principles of peptide fragmentation, we can explain up to 43% of the variation between ions fragmented by HCD and CID across an array of collision energy settings. We further show that in some circumstances, searching converted CID libraries can detect more peptides than searching existing CID libraries or libraries of machine learning predictions from FASTA databases. These results suggest that leveraging information in existing libraries by converting between HCD and CID libraries may be an effective interim solution while large-scale CID libraries are being developed.

An annual cycle of gene regulation in the red-legged salamander mental gland: from hypertrophy to expression of rapidly evolving pheromones.

BACKGROUND: Cell differentiation is mediated by synchronized waves of coordinated expression for hundreds to thousands of genes, and must be regulated to produce complex tissues and phenotypes. For many animal species, sexual selection has driven the development of elaborate male ornaments, requiring sex-specific differentiation pathways. One such male ornament is the pheromone-producing mental gland of the red-legged salamander (Plethodon shermani). Mental gland development follows an annual cycle of extreme hypertrophy, production of pheromones for the ~ 2 month mating season, and then complete resorption before repeating the process in the following year. At the peak of the mating season, the transcriptional and translational machinery of the mental gland are almost exclusively redirected to the synthesis of rapidly evolving pheromones. Of these pheromones, Plethodontid Modulating Factor (PMF) has experienced an unusual history: following gene duplication, the protein coding sequence diversified from positive sexual selection while the untranslated regions have been conserved by purifying selection. The molecular underpinnings that bridge the processes of gland hypertrophy, pheromone synthesis, and conservation of the untranslated regions remain to be determined. RESULTS: Using Illumina sequencing, we prepared a de novo transcriptome of the mental gland at six stages of development. Differential expression analysis and immunohistochemistry revealed that the mental gland initially adopts a highly proliferative, almost tumor-like phenotype, followed by a rapid increase in pheromone mRNA and protein. One likely player in this transition is Cold Inducible RNA Binding Protein (CIRBP), which selectively and cooperatively binds the highly conserved PMF 3' UTR. CIRBP, along with other proteins associated with stress response, have seemingly been co-opted to aid in mental gland development by helping to regulate pheromone synthesis. CONCLUSIONS: The P. shermani mental gland utilizes a complex system of transcriptional and post-transcriptional gene regulation to facilitate its hypertrophication and pheromone synthesis. The data support the evolutionary interplay of coding and noncoding segments in rapid gene evolution, and necessitate the study of co-evolution between pheromone gene products and their transcriptional/translational regulators. Additionally, the mental gland could be a powerful emerging model of regulated tissue proliferation and subsequent resorption within the dermis and share molecular links to skin cancer biology.

A Diverse Lipid Antigen-Specific TCR Repertoire Is Clonally Expanded during Active Tuberculosis.

Human T cells that recognize lipid Ags presented by highly conserved CD1 proteins often express semi-invariant TCRs, but the true diversity of lipid Ag-specific TCRs remains unknown. We use CD1b tetramers and high-throughput immunosequencing to analyze thousands of TCRs from ex vivo-sorted or in vitro-expanded T cells specific for the mycobacterial lipid Ag, glucose monomycolate. Our results reveal a surprisingly diverse repertoire resulting from editing of germline-encoded gene rearrangements analogous to MHC-restricted TCRs. We used a distance-based metric (TCRDist) to show how this diverse TCR repertoire builds upon previously reported conserved motifs by including subject-specific TCRs. In a South African cohort, we show that TCRDist can identify clonal expansion of diverse glucose monomycolate-specific TCRs and accurately distinguish patients with active tuberculosis from control subjects. These data suggest that similar mechanisms govern the selection and expansion of peptide and lipid Ag-specific T cells despite the nonpolymorphic nature of CD1.