Analyzing domain features of small proteins using a machine-learning method.

Small proteins (SPs) are a unique group of proteins that play crucial roles in many important biological processes. Exploring the biological function of SPs is necessary. In this study, the InterPro tool and the maximum correlation method were utilized to analyze functional domains of SPs.

Identification of methylation signatures and rules for predicting the severity of SARS-CoV-2 infection with machine learning methods.

Patients infected with SARS-CoV-2 at various severities have different clinical manifestations and treatments. Mild or moderate patients usually recover with conventional medical treatment, but severe patients require prompt professional treatment. Thus, stratifying infected patients for targeted treatment is meaningful.

Subcellular Localization Prediction of Human Proteins Using Multifeature Selection Methods.

Subcellular localization attempts to assign proteins to one of the cell compartments that performs specific biological functions. Finding the link between proteins, biological functions, and subcellular localization is an effective way to investigate the general organization of living cells in a systematic manner. However, determining the subcellular localization of proteins by traditional experimental approaches is difficult.

Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.

Neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease, and many other disease types, cause cognitive dysfunctions such as dementia via the progressive loss of structure or function of the body's neurons. However, the etiology of these diseases remains unknown, and diagnosing less common cognitive disorders such as vascular dementia (VaD) remains a challenge. In this work, we developed a machine-leaning-based technique to distinguish between normal control (NC), AD, VaD, dementia with Lewy bodies, and mild cognitive impairment at the microRNA (miRNA) expression level.

Recognition of Immune Cell Markers of COVID-19 Severity with Machine Learning Methods.

COVID-19 is hypothesized to be linked to the host's excessive inflammatory immunological response to SARS-CoV-2 infection, which is regarded to be a major factor in disease severity and mortality. Numerous immune cells play a key role in immune response regulation, and gene expression analysis in these cells could be a useful method for studying disease states, assessing immunological responses, and detecting biomarkers. Here, we developed a machine learning procedure to find biomarkers that discriminate disease severity in individual immune cells (B cell, CD4 cell, CD8 cell, monocyte, and NK cell) using single-cell gene expression profiles of COVID-19.

Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.

There are many types of cancers. Although they share some hallmarks, such as proliferation and metastasis, they are still very different from many perspectives. They grow on different organ or tissues.

Use of a Network-Based Method to Identify Latent Genes Associated with Hearing Loss in Children.

Hearing loss is a total or partial inability to hear. Approximately 5% of people worldwide experience this condition. Hearing capacity is closely related to language, social, and basic emotional development; hearing loss is particularly serious in children.

Identification of COVID-19 Infection-Related Human Genes Based on a Random Walk Model in a Virus-Human Protein Interaction Network.

Coronaviruses are specific crown-shaped viruses that were first identified in the 1960s, and three typical examples of the most recent coronavirus disease outbreaks include severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19. Particularly, COVID-19 is currently causing a worldwide pandemic, threatening the health of human beings globally. The identification of viral pathogenic mechanisms is important for further developing effective drugs and targeted clinical treatment methods.

Proteomic Profiling Exosomes from Vascular Smooth Muscle Cell.

Purpose: Vascular smooth muscle cells (VSMC) and endothelial cells (EC) communicate mutually to coordinate vascular development and homeostasis. Exosomes are emerging as one type of the mediators involved in this communication. Characterizing proteins in the exosomes is the critical first step in understanding how the VSMC-EC crosstalk is mediated by exosomes.

Alcohol drives -nitrosylation and redox activation of protein phosphatase 1, causing bovine airway cilia dysfunction.

Individuals with alcohol (ethanol)-use disorders are at increased risk for lung infections, in part, due to defective mucociliary clearance driven by motile cilia in the airways. We recently reported that isolated, demembranated bovine cilia (axonemes) are capable of producing nitric oxide (NO) when exposed to biologically relevant concentrations of alcohol. This increased presence of NO can lead to protein -nitrosylation, a posttranslational modification signaling mechanism involving reversible adduction of nitrosonium cations or NO to thiolate or thiyl radicals, respectively, of proteins forming -nitrosothiols (SNOs).

Functional proteomic analysis reveals the involvement of KIAA1199 in breast cancer growth, motility and invasiveness.

Background: KIAA1199 is a recently identified novel gene that is up-regulated in human cancer with poor survival. Our proteomic study on signaling polarity in chemotactic cells revealed KIAA1199 as a novel protein target that may be involved in cellular chemotaxis and motility. In the present study, we examined the functional significance of KIAA1199 expression in breast cancer growth, motility and invasiveness.

CDK1 phosphorylation of YAP promotes mitotic defects and cell motility and is essential for neoplastic transformation.

The Yes-associated protein, YAP, is a downstream effector of the Hippo pathway of cell-cycle control that plays important roles in tumorigenesis. Hippo-mediated phosphorylation YAP, mainly at S127, inactivates YAP function. In this study, we define a mechanism for positive regulation of YAP activity that is critical for its oncogenic function.

ISPTM: an iterative search algorithm for systematic identification of post-translational modifications from complex proteome mixtures.

Identifying protein post-translational modifications (PTMs) from tandem mass spectrometry data of complex proteome mixtures is a highly challenging task. Here we present a new strategy, named iterative search for identifying PTMs (ISPTM), for tackling this challenge. The ISPTM approach consists of a basic search with no variable modification, followed by iterative searches of many PTMs using a small number of them (usually two) in each search.

Quantitative phosphoproteomics analysis reveals broad regulatory role of heparan sulfate on endothelial signaling.

Heparan sulfate (HS) is a linear, abundant, highly sulfated polysaccharide that expresses in the vasculature. Recent genetic studies documented that HS critically modulates various endothelial cell functions. However, elucidation of the underlying molecular mechanism has been challenging because of the presence of a large number of HS-binding ligands found in the examined experimental conditions.

Application of chromosomal DNA and protein targeting for the identification of Yersinia pestis.

Purpose: A comprehensive strategy was developed and validated for the identification of pathogens from closely related near neighbors using both chromosomal and protein biomarkers, with emphasis on distinguishing Yersinia pestis from the ancestral bacterium Yersinia pseudotuberculosis.

Experimental Design: Computational analysis was used to discover chromosomal targets unique to Y. pestis.

Proteomic analysis of the organ of corti using nanoscale liquid chromatography coupled with tandem mass spectrometry.

The organ of Corti (OC) in the cochlea plays an essential role in auditory signal transduction in the inner ear. For its minute size and trace amount of proteins, the identification of the molecules in pathophysiologic processes in the bone-encapsulated OC requires both delicate separation and a highly sensitive analytical tool. Previously, we reported the development of a high resolution metal-free nanoscale liquid chromatography system for highly sensitive phosphoproteomic analysis.

Quantitative proteomics reveals that miR-155 regulates the PI3K-AKT pathway in diffuse large B-cell lymphoma.

The aberrant expression of microRNA-155 (miR-155), which has emerged as having a significant impact on the biological characteristics of lymphocytes, plays important roles in B-cell malignancies, such as diffuse large B-cell lymphoma (DLBCL). DLBCL is the most common non-Hodgkin's lymphoma in the adult population, accounting for approximately 40% of newly diagnosed non-Hodgkin's lymphoma cases globally. To determine the specific function of miR-155, a quantitative proteomics approach was applied to examine the inhibitory effects of miR-155 on protein synthesis in DLBCL cells.

Development and application of site-specific proteomic approach for study protein S-nitrosylation.

Protein S-nitrosylation is the covalent redox-related modification of cysteine sulfhydryl groups with nitric oxide, creating a regulatory impact similar to phosphorylation. Recent studies have reported a growing number of proteins to be S-nitrosylated in vivo resulting in altered functions. These studies support S-nitrosylation as a critical regulatory mechanism, fine-tuning protein activities within diverse cellular processes and biochemical pathways.

Quantitative proteomic analysis of mouse embryonic fibroblasts and induced pluripotent stem cells using 16O/18O labeling.

Induced pluripotent stem cells (iPSC) hold great promise for regenerative medicine as well as for investigations into the pathogenesis and treatment of various diseases. Understanding of key intracellular signaling pathways and protein targets that control development of iPSC from somatic cells is essential for designing new approaches to improve reprogramming efficiency. Here, we report the development and application of an integrated quantitative proteomics platform for investigating differences in protein expressions between mouse embryonic fibroblasts (MEF) and MEF-derived iPSC.

Software for quantitative proteomic analysis using stable isotope labeling and data independent acquisition.

Many software tools have been developed for analyzing stable isotope labeling (SIL)-based quantitative proteomic data using data dependent acquisition (DDA). However, programs for analyzing SIL-based quantitative proteomics data obtained with data independent acquisition (DIA) have yet to be reported. Here, we demonstrated the development of a new software for analyzing SIL data using the DIA method.

Inhibition of phosphorylated c-Met in rhabdomyosarcoma cell lines by a small molecule inhibitor SU11274.

Background: c-Met is a receptor tyrosine kinase (RTK) that is over-expressed in a variety of cancers and involved in cell growth, invasion, metastasis and angiogenesis. In this study, we investigated the role of c-Met in rhabdomyosarcoma (RMS) using its small molecule inhibitor SU11274, which has been hypothesized to be a potential therapeutic target for RMS.

Methods: The expression level of phosphorylated c-Met in RMS cell lines (RD, CW9019 and RH30) and tumor tissues was assessed by phospho-RTK array and immunohistochemistry, respectively.

Histone acetyltransferase p300 acetylates Pax5 and strongly enhances Pax5-mediated transcriptional activity.

Pax5/B cell lineage specific activator protein (BSAP) is a B lineage-specific regulator that controls the B lineage-specific gene expression program and immunoglobulin gene V(H) to DJ(H) recombination. Despite extensive studies on its multiple functions, little is known about how the activity of Pax5 is regulated. Here, we show that co-expression of histone acetyltransferase E1A binding protein p300 dramatically enhances Pax5-mediated transcriptional activation.

UNiquant, a program for quantitative proteomics analysis using stable isotope labeling.

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling.

Site-specific proteomics approach for study protein S-nitrosylation.

Here we present a novel and robust method for the identification of protein S-nitrosylation sites in complex protein mixtures. The approach utilizes the cysteinyl affinity resin to selectively enrich S-nitrosylated peptides reduced by ascorbate followed by nanoscale liquid chromatography tandem mass spectrometry. Two alkylation agents with different added masses were employed to differentiate the S-nitrosylation sites from the non-S-nitrosylation sites.