Project description:Mass spectrometry enables global analysis of posttranslationally modified proteoforms from biological samples, yet we still lack methods to systematically predict, or even prioritize, which modification sites may perturb protein function. Here we describe a proteomic method, Hotspot Thermal Profiling, to detect the effects of site-specific protein phosphorylation on the thermal stability of thousands of native proteins in live cells. This massively parallel biophysical assay unveiled shifts in overall protein stability in response to site-specific phosphorylation sites, as well as trends related to protein function and structure. This method can detect intrinsic changes to protein structure as well as extrinsic changes to protein-protein and protein-metabolite interactions resulting from phosphorylation. Finally, we show that functional 'hotspot' protein modification sites can be discovered and prioritized for study in a high-throughput and unbiased fashion. This approach is applicable to diverse organisms, cell types and posttranslational modifications.
Project description:Technique advances in proteomics including sample separation, mass spectrometry and searching algorithm have empowered in-depth discovery of protein post-translational modifications from biological samples. Instead, there is still a relative delay in the systematic researches for functional significance of these modifications. Herein, we propose Refined-TPP, a novel methodology for thermal proteomics, to systematically examine the effects of site-specific modification on the thermal stability of native proteins. This globally biophysical assay bridges the gap between the structural modifications and their functional impacts on proteins, and provides here a robust platform for the first time to effectively interrogate the functional implications for N-glycosylation. Finally, we elucidated the pivotal roles of explored N-glycosylation in protein structure and function, including protein stability, subcellular localization and enzyme activity. This novel strategy is readily applicable in a high-throughput and unbiased manner to further investigations for diverse objects, including drug-target screening, protein interactions and other functional PTMs exploration.
Project description:Epigenetic mechanisms such as histone modifications and DNA methylation form a critical layer of control that regulates gene activities. Histone modifications play critical roles in adaptive tuning of chromatin structures. Profiling various histone modifications at the genome scale using primary tissues from animal and human samples is an important step for functional studies of epigenomes and epigenomics-based precision medicine. Because the profile of a histone mark is highly specific to a particular cell type, isolation of a cell type of interest from primary tissues is often necessary to generate a homogeneous cell population and such operation tends to yield a low number of cells. In addition, high-throughput processing is desired in such effort due to the number of histone marks of interests and the potential volume of samples in a hospital setting. In this protocol, we describe detailed information on device fabrication, setup, and operation of microfluidic oscillatory washing-based chromatin immunoprecipitation followed by sequencing (MOWChIP-seq) for profiling histone modifications using as few as 30-100 cells per assay with a throughput as high as 8 assays in a run. The critical step of MOWChIP-seq operation involves flowing of chromatin fragments through a packed bed of antibody-coated beads followed by a vigorous microfluidic oscillatory washing. The ChIP process is semi-automated for reduced labor and improved reproducibility. We have used the protocol to study a number of histone modifications in various types of mouse and human tissue types ranging from isolated nuclei of brain cells to cell subtypes isolated from human breast tissues.
Project description:Biomarker microarrays are becoming valuable tools for serological screening of disease-associated autoantibodies. Post-translational modifications (PTMs) such as glycosylation extend the range of protein function, and a variety of glycosylated proteins are known to be altered in disease progression. Here, we have developed a synthetic screening microarray platform for facile display of O-glycosylated peptides (O-PTMs). By introduction of a capping step during chemical solid-phase glycopeptide synthesis, selective enrichment of N-terminal glycopeptide end products was achieved on an amine-reactive hydrogel-coated microarray glass surface, allowing high-throughput display of large numbers of glycopeptides. Utilizing a repertoire of recombinant glycosyltransferases enabled further diversification of the array libraries in situ and display of a new level of potential biomarker candidates for serological screening. As proof-of-concept, we have demonstrated that MUC1 glycopeptides could be assembled and used to detect autoantibodies in vaccine-induced disease-free breast cancer patients and in patients with confirmed disease at time of diagnosis.
Project description:The development of new drugs is multidisciplinary and systematic work. High-throughput techniques based on "-omics" have driven the discovery of biomarkers in diseases and therapeutic targets of drugs. A transcriptome is the complete set of all RNAs transcribed by certain tissues or cells at a specific stage of development or physiological condition. Transcriptome research can demonstrate gene functions and structures from the whole level and reveal the molecular mechanism of specific biological processes in diseases. Currently, gene expression microarray and high-throughput RNA-sequencing have been widely used in biological, medical, clinical, and drug research. The former has been applied in drug screening and biomarker detection of drugs due to its high throughput, fast detection speed, simple analysis, and relatively low price. With the further development of detection technology and the improvement of analytical methods, the detection flux of RNA-seq is much higher but the price is lower, hence it has powerful advantages in detecting biomarkers and drug discovery. Compared with the traditional RNA-seq, scRNA-seq has higher accuracy and efficiency, especially the single-cell level of gene expression pattern analysis can provide more information for drug and biomarker discovery. Therefore, (sc)RNA-seq has broader application prospects, especially in the field of drug discovery. In this overview, we will review the application of these technologies in drug, especially in natural drug and biomarker discovery and development. Emerging applications of scRNA-seq and the third generation RNA-sequencing tools are also discussed.
Project description:Drug development is plagued by inefficiency and high costs due to issues such as inadequate drug efficacy and unexpected toxicity. Mass spectrometry (MS)-based proteomics, particularly isobaric quantitative proteomics, offers a solution to unveil resistance mechanisms and unforeseen side effects related to off-targeting pathways. Thermal proteome profiling (TPP) has gained popularity for drug target identification at the proteome scale. However, it involves experiments with multiple temperature points, resulting in numerous samples and considerable variability in large-scale TPP analysis. We propose a high-throughput drug target discovery workflow that integrates single-temperature TPP, a fully automated proteomics sample preparation platform (autoSISPROT), and Data Independent Acquisition (DIA) quantification. The autoSISPROT platform enables the simultaneous processing of 96 samples in less than 2.5 hours, achieving protein digestion, desalting, and optional TMT labeling (requires an additional 1 hour) with 96-channel all-in-tip operations. The results demonstrated excellent sample preparation performance with >94% digestion efficiency, >98% TMT labeling efficiency, and >0.9 of intraand inter-batch Pearson correlation coefficients. By automatically processing 87 samples, we identified both known targets and potential off-targets of 20 kinase inhibitors, affording over a 10-fold improvement in throughput compared to classical TPP. This fully automated workflow offers a high-throughput solution for proteomics sample preparation and drug target/off-target identification.
Project description:miRNAs are small, non-coding RNA that negatively regulate gene expression at post-transcriptional level, which play crucial roles in various physiological and pathological processes, such as development and tumorigenesis. Although deep sequencing technologies have been applied to investigate various small RNA transcriptomes, their computational methods are far away from maturation as compared to microarray-based approaches. In this study, a comprehensive web server mirTools was developed to allow researchers to comprehensively characterize small RNA transcriptome. With the aid of mirTools, users can: (i) filter low-quality reads and 3/5' adapters from raw sequenced data; (ii) align large-scale short reads to the reference genome and explore their length distribution; (iii) classify small RNA candidates into known categories, such as known miRNAs, non-coding RNA, genomic repeats and coding sequences; (iv) provide detailed annotation information for known miRNAs, such as miRNA/miRNA*, absolute/relative reads count and the most abundant tag; (v) predict novel miRNAs that have not been characterized before; and (vi) identify differentially expressed miRNAs between samples based on two different counting strategies: total read tag counts and the most abundant tag counts. We believe that the integration of multiple computational approaches in mirTools will greatly facilitate current microRNA researches in multiple ways. mirTools can be accessed at http://centre.bioinformatics.zj.cn/mirtools/ and http://59.79.168.90/mirtools.