Project description:Substantial efforts are underway to deepen our understanding of human brain morphology, structure, and function using high-resolution imaging as well as high-content molecular profiling technologies. The current work adds to these approaches by providing a comprehensive and quantitative protein expression map of 13 anatomically distinct brain regions covering more than 11,000 proteins. This was enabled by the optimization, characterization, and implementation of a high-sensitivity and high-throughput microflow liquid chromatography timsTOF tandem mass spectrometry system (LC-MS/MS) capable of analyzing more than 2,000 consecutive samples prepared from formalin-fixed paraffin embedded (FFPE) material. Analysis of this proteomic resource highlighted brain region-enriched protein expression patterns and functional protein classes, protein localization differences between brain regions and individual markers for specific areas. To facilitate access to and ease further mining of the data by the scientific community, all data can be explored online in a purpose-built R Shiny app (https://brain-region-atlas.proteomics.ls.tum.de).
Project description:Constructing high-quality haplotype-resolved genome assemblies has substantially improved the ability to detect and characterize genetic variants. A targeted approach providing readily access to the rich information from haplotype-resolved genome assemblies will be appealing to groups of basic researchers and medical scientists focused on specific genomic regions. Here, using the 4.5 megabase, notoriously difficult-to-assemble major histocompatibility complex (MHC) region as an example, we demonstrated an approach to construct haplotype-resolved assembly of the targeted genomic region with the CRISPR-based enrichment. Compared to the results from haplotype-resolved genome assembly, our targeted approach achieved comparable completeness and accuracy with reduced computing complexity, sequencing cost, as well as the amount of starting materials. Moreover, using the targeted assembled personal MHC haplotypes as the reference both improves the quantification accuracy for sequencing data and enables allele-specific functional genomics analyses of the MHC region. Given its highly efficient use of resources, our approach can greatly facilitate population genetic studies of targeted regions, and may pave a new way to elucidate the molecular mechanisms in disease etiology.
Project description:Constructing high-quality haplotype-resolved genome assemblies has substantially improved the ability to detect and characterize genetic variants. A targeted approach providing readily access to the rich information from haplotype-resolved genome assemblies will be appealing to groups of basic researchers and medical scientists focused on specific genomic regions. Here, using the 4.5 megabase, notoriously difficult-to-assemble major histocompatibility complex (MHC) region as an example, we demonstrated an approach to construct haplotype-resolved assembly of the targeted genomic region with the CRISPR-based enrichment. Compared to the results from haplotype-resolved genome assembly, our targeted approach achieved comparable completeness and accuracy with reduced computing complexity, sequencing cost, as well as the amount of starting materials. Moreover, using the targeted assembled personal MHC haplotypes as the reference both improves the quantification accuracy for sequencing data and enables allele-specific functional genomics analyses of the MHC region. Given its highly efficient use of resources, our approach can greatly facilitate population genetic studies of targeted regions, and may pave a new way to elucidate the molecular mechanisms in disease etiology.
Project description:To understand the complexity of the brain, connectome and transcriptome maps of high resolution are being generated, but an equivalent catalogue of the brain proteome is lacking. To provide a starting point, we have performed an in-depth proteome analysis of the adult mouse brain, its major regions and cell types, which resulted in the so far largest collection of cell-type resolved protein expression data of the brain. Comparisons of the 12,934 identified proteins in oligodendrocytes, astrocytes, microglia and cortical neurons with deep sequencing data of the transcriptome indicated deep coverage of the proteome. We identified novel protein makers for different cell type and brain regions. These were validated either directly such as in case of cell types or by comparative analysis against Allen mouse brain atlas. The utility and the power of the resource were demonstrated by the identification of Lsamp, an adhesion molecule of the IgLON family, as a negative regulator of myelination in a subpopulation of neurons. Our in-depth proteome analysis of CNS cell types provides a framework towards a system-level understanding of cell type diversity in the CNS and serves as a rich resource to the neuroscience community for the better understanding of brain development and function.
Project description:Allelic differences between the two sets of chromosomes can affect the propensity of inheritance in humans, but the extent of such differences in the human genome has yet to be fully explored. Here, we delineate allelic chromatin modifications and transcriptomes amongst a broad set of human tissues, enabled by a chromosome-span haplotype reconstruction strategy1. The resulting haplotype-resolved epigenomic maps reveal extensive allele bias in the transcription of human genes as well as chromatin state, allowing us to infer cis-regulatory relationships between genes and their control sequences. These maps also uncover a new class of cis regulatory elements and detail activities of repetitive elements in various human tissues. The rich datasets described here will enhance our understanding of the mechanisms controlling tissue-specific gene expression programs. One replicate of Hi-C experiment in four human tissues with four different individuals (Thymus STL001, Aorta STL002, Leftventricle STL003, and Liver STL011).
Project description:Mass spectrometry (MS) has emerged as a valuable tool for plasma proteome profiling and disease biomarker discovery. However, wide range of plasma protein concentrations along with technical and biological variabilities, continue to present significant challenges for deep and reproducible protein quantitation across large patient cohorts. Here we demonstrate the qualitative and quantitative performance gain of the timsTOF HT over the timsTOF Pro 2 mass spectrometer in the analysis of neat (unfractionated) and Proteograph™ (PG)-processed plasma across a wide range of peptide loading masses and liquid chromatography (LC) gradients. We observed up to a 76% increase in total plasma peptide precursors identified and a >2-fold boost in quantifiable plasma peptide precursors (CV<20%) with timsTOF HT compared to timsTOF Pro 2. In an exploratory study of 20 late-stage cancer and 20 control sampleswe observed a ~50% increase in total and statistically significant plasma peptide precursors (q<0.05) with timsTOF HT compared to Pro 2. Our data demonstrated the superior performance of timsTOF HT in identifying and quantifying differences between biologically diverse samples, which can improve disease biomarker discovery in large cohort studies. Moreover, researchers can leverage datasets from this study to optimize their LCMS workflows for plasma protein profiling and biomarker discovery. See the details in a paper, entitled "timsTOF HT improves protein identification and quantitative reproducibility for deep unbiased plasma protein biomarker discovery".
Project description:Mass spectrometry (MS) has emerged as a valuable tool for plasma proteome profiling and disease biomarker discovery. However, wide range of plasma protein concentrations along with technical and biological variabilities, continue to present significant challenges for deep and reproducible protein quantitation across large patient cohorts. Here we demonstrate the qualitative and quantitative performance gain of the timsTOF HT over the timsTOF Pro 2 mass spectrometer in the analysis of neat (unfractionated) and Proteograph™ (PG)-processed plasma across a wide range of peptide loading masses and liquid chromatography (LC) gradients. We observed up to a 76% increase in total plasma peptide precursors identified and a >2-fold boost in quantifiable plasma peptide precursors (CV<20%) with timsTOF HT compared to timsTOF Pro 2. In an exploratory study of 20 late-stage cancer and 20 control sampleswe observed a ~50% increase in total and statistically significant plasma peptide precursors (q<0.05) with timsTOF HT compared to Pro 2. Our data demonstrated the superior performance of timsTOF HT in identifying and quantifying differences between biologically diverse samples, which can improve disease biomarker discovery in large cohort studies. Moreover, researchers can leverage datasets from this study to optimize their LCMS workflows for plasma protein profiling and biomarker discovery. See the details in a paper, entitled "timsTOF HT improves protein identification and quantitative reproducibility for deep unbiased plasma protein biomarker discovery".
Project description:Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with poor prognosis and limited treatment options. Efforts to identify effective treatments are thwarted by limited understanding of IPF pathogenesis and poor translatability of available preclinical models. To address these limitations, we generated spatially resolved transcriptome maps of human IPF and bleomycin-induced mouse lung fibrosis.
Project description:The heart is a central human organ and its diseases are the leading cause of death worldwide, but an in-depth knowledge of the identity and quantity of its constituent proteins is still lacking. Here, we determine the healthy human heart proteome by measuring 16 anatomical regions and three major cardiac cell types by high-resolution mass spectrometry-based proteomics. From low microgram sample amounts, we quantify over 10,700 proteins in this high dynamic range tissue. We combine copy numbers per cell with protein organellar assignments to build a model of the heart proteome at the subcellular level. Analysis of cardiac fibroblasts identifies cellular receptors as potential cell surface markers. Application of our heart map to atrial fibrillation reveals individually distinct mitochondrial dysfunctions. The heart map is available at maxqb.biochem.mpg.de as a resource for future analyses of normal heart function and disease.
Project description:Coronavirus disease 2019 (COVID-19) induces diverse clinical manifestations accompanied by multi-organ dysfunction. Of these, heart complications are the most life threatening. Direct myocardial and vascular injuries due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) drive systemic inflammation, which is the leading cause of acute cardiac injury associated with COVID-19. However, in-depth knowledge of the injury characteristics and quantity of its constituent proteins, as well as specific functions of four heart regions, including two ventricles and atria, is lacking. Here, through a strategy for spatial quantitative proteomics by combining comparative anatomy, laser-capture microdissection, and mass spectrometry, we successfully established a complete region-resolved heart proteome map by myocardia and microvessels from four regions of the hearts. We analyzed the dysfunction of different regions of COVID-19 patients’ native heart tissues in situ with histological examinaton. Focusing on the molecular features of myocardial and microvessel tissues with obvious inflammatory cells, a series of specific molecular dysfunctions of myocardium and microvessel were located in different cardiac regions caused by inflammation. These results could provide guidance for future discovery of improved clinical treatments for heart diseases.