Biology subjects

Jaffe, J.

Publications and source records attributed to Jaffe, J..

8 recordsLinked to original sources

bioRxiv2022

High Angular Resolution Susceptibility Imaging and Estimation of Fiber Orientation Distribution Functions in Primate Brain

Uncovering brain-tissue microstructure including axonal characteristics is a major neuroimaging research focus. Within this scope, anisotropic properties of magnetic susceptibility in white matter have been successfully employed to estimate primary axonal trajectories using mono-tensorial models. However, anisotropic susceptibility has not yet been considered for modeling more complex fiber structures within a voxel, such as intersecting bundles, or an estimation of orientation distribution functions (ODFs). This information is routinely obtained by high angular resolution diffusion imaging (HARDI) techniques. In applications to fixed tissue, however, diffusion-weighted imaging suffers from an inherently low signal-to-noise ratio and limited spatial resolution, leading to high demands on the performance of the gradient system in order to mitigate these limitations. In the current work, high angular resolution susceptibility imaging (HARSI) is proposed as a novel, phase-based methodology to estimate ODFs. A multiple gradient-echo dataset was acquired in an entire fixed chimpanzee brain at 61 orientations by reorienting the specimen in the magnetic field. The constant solid angle method was adapted for estimating phase-based ODFs. HARDI data were also acquired for comparison. HARSI yielded information on whole-brain fiber architecture, including identification of peaks of multiple bundles that resembled features of the HARDI results. Distinct differences between both methods suggest that susceptibility properties may offer complementary microstructural information. These proof-of-concept results indicate a potential to study the axonal organization in post-mortem primate and human brain at high resolution. HighlightsO_LIIntroduction of High Angular Resolution Susceptibility Imaging (HARSI) for advancing Quantitative Susceptibility Mapping (QSM). C_LIO_LIHARSI-derived fiber orientation distributions in fixed chimpanzee brain. C_LIO_LIHARSI-based visualization of complex fiber configurations. C_LIO_LIComparisons between HARSI and High Angular Resolution Diffusion Imaging. C_LIO_LIPotential for high-resolution post-mortem imaging of fiber architecture. C_LI

neuroscience↗

bioRxiv2021

A LINCS microenvironment perturbation resource for integrative assessment of ligand-mediated molecular and phenotypic responses

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods (synapse.org/LINCS_MCF10A). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes.

systems biology↗

bioRxiv2019

piNET: a versatile web platform for downstream analysis and visualization of proteomics data

Large proteomics data, including those generated by mass spectrometry, are being generated to characterize biological systems at the protein level. Computational methods and tools to identify and quantify peptides, proteins and post-translational modifications (PTMs) that are captured in modern mass spectrometers have matured over the years. On the other hand, tools for downstream analysis, interpretation and visualization of proteomics data sets, in particular those involving PTMs, require further improvement and integration to accelerate scientific discovery and maximize the impact of proteomics studies by connecting them better with biological knowledge across not only proteomics, but also other Omics domains. With the goal of addressing these challenges, the piNET server has been developed as a versatile web platform to facilitate mapping, annotation, analysis and visualization of peptide, PTM, and protein level quantitative data generated by either targeted, shotgun or other proteomics approaches. Building on our experience with large scale analysis of gene and protein expression profiles as part of the Library of Integrated Network Cellular Signatures (LINCS) project, piNET has been designed as a fast, versatile and easy to use web-based tool with three modules that provide mapping from peptides (with PTMs) to proteins, from PTM sites to modifying enzymes that target those sites, and finally from proteins (with PTMs) to pathways, and for further mechanistic insights to LINCS signatures of chemical and genetic perturbations. piNET is freely available at http://www.pinet-server.org.

bioinformatics↗

bioRxiv2019

The UTX Tumor Suppressor Directly Senses Oxygen to Control Chromatin and Cell Fate

Mammalian cells express multiple 2-oxoglutarate (OG)-dependent dioxygenases, including many chromatin regulators. The oxygen affinities, and hence oxygen sensing capabilities, of the 2-oxoglutarate (OG)-dependent dioxygenases reported to date vary widely. Hypoxia can affect chromatin, but whether this reflects a direct effect on chromatin-modifying dioxygenases, or indirect effects caused by the hypoxic-induction of the HIF transcription factor or the endogenous 2-OG competitor 2-hydroxyglutarate (2-HG), is unclear. Here we report that hypoxia induces a HIF- and 2-HG-independent histone modification signature consistent with KDM inactivation. We also show that the H3K27 histone demethylase KDM6A (also called UTX), but not its paralog KDM6B, is oxygen-sensitive. KDM6A loss, like hypoxia, prevented H3K27me3 erasure and blocked differentiation. Conversely, restoring H3K27me3 homeostasis in hypoxic cells reversed these effects. Therefore, oxygen directly affects chromatin regulators to control cell fate.\n\nOne Sentence SummaryKDM6A demethylase activity is diminished under hypoxic conditions and causes changes in gene expression programs that govern cell fate.

biochemistry↗

bioRxiv2017

A unified web platform for network-based analyses of genomic data

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to quantitatively compare the signal-to-noise ratio of different networks, the biology they describe, and to identify the optimal network to interpret a particular genetic dataset. Via GeNets users can train a machine-learning model (Quack) to make such comparisons; and they can execute, store, and share analyses of genetic and RNA sequencing datasets.

genomics↗

bioRxiv2017

A Library of Phosphoproteomic and Chromatin Signatures for Characterizing Cellular Responses to Drug Perturbations

Though the added value of proteomic measurements to gene expression profiling has been demonstrated, profiling of gene expression on its own remains the dominant means of understanding cellular responses to perturbation. Direct protein measurements are typically limited due to issues of cost and scale; however, the recent development of high-throughput, targeted sentinel mass spectrometry assays provides an opportunity for proteomics to contribute at a meaningful scale in high-value areas for drug development. To demonstrate the feasibility of a systematic and comprehensive library of perturbational proteomic signatures, we profiled 90 drugs (in triplicate) in six cell lines using two different proteomic assays -- one measuring global changes of epigenetic marks on histone proteins and another measuring a set of peptides reporting on the phosphoproteome -- for a total of more than 3,400 samples. This effort represents a first-of-its-kind resource for proteomics. The majority of tested drugs generated reproducible responses in both phosphosignaling and chromatin states, but we observed differences in the responses that were cell line-and assay-specific. We formalized the process of comparing response signatures within the data using a concept called connectivity, which enabled us to integrate data across cell types and assays. Furthermore, it facilitated incorporation of transcriptional signatures. Consistent connectivity among cell types revealed cellular responses that transcended cell-specific effects, while consistent connectivity among assays revealed unexpected associations between drugs that were confirmed by experimental follow-up. We further demonstrated how the resource could be leveraged against public domain external datasets to recognize therapeutic hypotheses that are consistent with ongoing clinical trials for the treatment of multiple myeloma and acute lymphocytic leukemia (ALL). These data are available for download via the Gene Expression Omnibus (accession GSE101406), and web apps for interacting with this resource are available at https://clue.io/proteomics.\n\nHighlightsO_LIFirst-of-its-kind public resource of proteomic responses to systematically administered perturbagens\nC_LIO_LIDirect proteomic profiling of phosphosignaling and chromatin states in cells for 90 drugs in six different cell lines\nC_LIO_LIExtends Connectivity Map concept to proteomic data for integration with transcriptional data\nC_LIO_LIEnables recognition of unexpected, cell type-specific activities and potential translational therapeutic opportunities\nC_LI

systems biology↗

bioRxiv2017

Quantifying homologous proteins and proteoforms

Many proteoforms - arising from alternative splicing, post-translational modifications (PTMs), or paralogous genes - have distinct biological functions, such as histone PTM proteoforms. However, their quantification by existing bottom-up mass-spectrometry (MS) methods is undermined by peptide-specific biases. To avoid these biases, we developed and implemented a first-principles model (HIquant) for quantifying proteoform stoichiometries. We characterized when MS data allow inferring proteoform stoichiometries by HIquant, derived an algorithm for optimal inference, and demonstrated experimentally high accuracy in quantifying fractional PTM occupancy without using external standards, even in the challenging case of the histone modification code. A HIquant server is implemented at: https://web.northeastern.edu/slavov/2014_HIquant/

systems biology↗

bioRxiv2017

The influence of higher-order epistasis on biological fitness landscape topography

The effect of a mutation on the organism often depends on what other mutations are already present in its genome. Geneticists refer to such mutational interactions as epistasis. Pairwise epistatic effects have been recognized for over a century, and their evolutionary implications have received theoretical attention for nearly as long. However, pairwise epistatic interactions themselves can vary with genomic background. This is called higher-order epistasis, and its consequences for evolution are much less well understood. Here, we assess the influence that higher-order epistasis has on the topography of 16 published, biological fitness landscapes. We find that on average, their effects on fitness landscape declines with order, and suggest that notable exceptions to this trend may deserve experimental scrutiny. We explore whether natural selection may have contributed to this finding, and conclude by highlight opportunities for further work dissecting the influence that epistasis of all orders has on the efficiency of natural selection.

evolutionary biology↗