Biology subjects

Diaz, D.

Publications and source records attributed to Diaz, D..

22 records · Page 2Linked to original sources

bioRxiv2020

Antibody recognition of the Pneumovirus fusion protein trimer interface

Human metapneumovirus is a leading cause of viral respiratory infection in children, and can cause severe lower respiratory infection in infants, the elderly, and immunocompromised patients. However, there remain no licensed vaccines or specific treatments for hMPV infection. Although the hMPV fusion (F) protein is the sole target of neutralizing antibodies, the immunological properties of hMPV F are still poorly understood. To further define the humoral immune response to the hMPV F protein, we isolated two new human monoclonal antibodies (mAbs), MPV458 and MPV465. Both mAbs are neutralizing in vitro and target a unique antigenic site harbored within the trimeric interface of the hMPV F protein. We determined both MPV458 and MPV465 have higher affinity for monomeric hMPV F than trimeric hMPV F. MPV458 was co-crystallized with hMPV F, and the mAb primarily interacts with an alpha helix on the F2 region of the hMPV F protein. Surprisingly, the major epitope for MPV458 lies within the trimeric interface of the hMPV F protein, suggesting significant breathing of the hMPV F protein must occur for hMPV F protein recognition of the novel epitope. In addition, significant glycan interactions were observed with a somatically mutated light chain framework residue. The data presented identifies a novel epitope on the hMPV F protein for structure-based vaccine design, and provides a new mechanism for human antibody neutralization of viral glycoproteins.

immunology↗

bioRxiv2019

Identification and Characterization of the First Fragment Hits for SETDB1 Tudor Domain

SET domain bifurcated protein 1 (SETDB1) is a human histone-lysine methyltransferase, which is amplified in human cancers and was shown to be crucial in the growth of non-small and small cell lung carcinoma. In addition to its catalytic domain, SETDB1 harbors a unique tandem tudor domain which recognizes histone sequences containing both methylated and acetylated lysines, and likely contributes to its localization on chromatin. Using X-ray crystallography and NMR spectroscopy fragment screening approaches, we have identified the first small molecule fragment hits that bind to histone peptide binding groove of the TTD of SETDB1. Herein, we describe the binding modes of these fragments and analogues and the biophysical characterization of key compounds. These confirmed small molecule fragments will inform the development of potent antagonists of SETDB1 interaction with histones.

pharmacology and toxicology↗

bioRxiv2018

Computational Disease Subtyping based on Joint Analysis of Clinical and Genomic Data

ObjectiveTo investigate application of non-negative tensor decomposition for disease subtype discovery based on joint analysis of clinical and genomic data.\n\nData and MethodsSomatic mutation profiles including 11,996 genes of 503 breast cancer patients from the Cancer Genome Atlas (TCGA) along with 11 clinical variables and markers of these patients were used to construct a binary third-order tensor. CANDECOMP/PARAFAC method was applied to decompose the constructed tensor into rank-one component tensors. Definitions of breast cancer verotypes were constructed from the patient, gene and clinical vectors corresponding to each component tensor. Patient membership proportions in the identified verotypes were utilized in a Cox proportional hazards model to predict their survival.\n\nResultsQualitative evaluation of the verotypes obtained by tensor factorization indicates that they correspond to clinically meaningful breast cancer subtypes. While some components correspond to the known HER2- or ER-positive breast cancer subtypes, other components correspond to a variant of triple negative subtype and a cohort of patients with high mutation load of tumor suppressor genes. Quantitative evaluation indicates that the Cox model utilizing computationally discovered breast cancer verotypes is more accurate (AUC=0.5796) at predicting patient survival than the Cox models utilizing random patient membership proportions in cancer subtypes (AUC=0.4056) as well as patient membership proportions in genotypes (AUC=0.4731) and phenotypes (AUC=0.5047) obtained by non-negative factorization of the somatic mutation and clinical matrices.\n\nConclusionNon-negative factorization of a binary tensor constructed from clinical and genomic data enables high-throughput discovery of breast cancer verotypes that are effective at predicting patient survival.

bioinformatics↗

bioRxiv2018

Glial cells in the heart? Replicating the diversity of the myocardium with low-cost 3D models

Excitation-contraction (EC) coupling in the heart has, until recently, been solely accredited to cardiomyocytes. The inherent complexities of the heart make it difficult to examine nonmuscle contributions to contraction in vivo, and conventional in vitro models fail to capture multiple features and cellular heterogeneity of the myocardium. Here, we report on the development of a 3D cardiac Tissue towards recapitulating the architecture and composition of native myocardium in vitro. Cells are encapsulated within micropatterned gelatin-based hydrogels formed via visible light photocrosslinking. This system enables spatial control of cardiac microarchitecture, perturbation of the cellular composition, and functional measures of EC coupling via video microscopy and a custom algorithm to quantify beat frequency and degree of coordination. To demonstrate the robustness of these tools and evaluate the impact of altered cell population densities on cardiac Tissues, contractility and cell morphology were assessed with the inclusion of exogenous non-myelinating Schwann cells (SCs). Results demonstrate that the addition of exogenous SCs alter cardiomyocyte EC, profoundly inhibiting the response to electrical pacing. Computational modeling of connexin-mediated coupling suggests that SCs impact cardiomyocyte resting potential and rectification following depolarization. Cardiac Tissues hold potential for examining the role of cellular heterogeneity in heart health, pathologies, and cellular therapies.

bioengineering↗