Temporal and Sex-Linked Protein Expression Dynamics in a Familial Model of Alzheimer's Disease.

Mouse models of Alzheimer's disease (AD) show progression through stages reflective of human pathology. Proteomics identification of temporal and sex-linked factors driving AD-related pathways can be used to dissect initiating and propagating events of AD stages to develop biomarkers or design interventions. In the present study, we conducted label-free proteome measurements of mouse hippocampus tissue with variables of time (3, 6, and 9 months), genetic background (5XFAD versus WT), and sex (equal males and females). These time points are associated with well-defined phenotypes with respect to the following: Aß42 plaque deposition, memory deficits, and neuronal loss, allowing correlation of proteome-based molecular signatures with the mouse model stages. Our data show 5XFAD mice exhibit increases in known human AD biomarkers as amyloid-beta peptide, APOE, GFAP, and ITM2B are upregulated across all time points/stages. At the same time, 23 proteins are here newly associated with Alzheimer's pathology as they are also dysregulated in 5XFAD mice. At a pathways level, the 5XFAD-specific upregulated proteins are significantly enriched for DNA damage and stress-induced senescence at 3-month only, while at 6-month, the AD-specific proteome signature is altered and significantly enriched for membrane trafficking and vesicle-mediated transport protein annotations. By 9-month, AD-specific dysregulation is also characterized by significant neuroinflammation with innate immune system, platelet activation, and hyper-reactive astrocyte-related enrichments. Aside from these temporal changes, analysis of sex-linked differences in proteome signatures uncovered novel sex and AD-associated proteins. Pathway analysis revealed sex-linked differences in the 5XFAD model to be involved in the regulation of well-known human AD-related processes of amyloid fibril formation, wound healing, lysosome biogenesis, and DNA damage. Verification of the discovery results by Western blot and parallel reaction monitoring confirm the fundamental conclusions of the study and poise the 5XFAD model for further use as a molecular tool for understanding AD.

Making proteomics accessible: RokaiXplorer for interactive analysis of phospho-proteomic data.

Summary: We present RokaiXplorer, an intuitive web tool designed to address the scarcity of user-friendly solutions for proteomics and phospho-proteomics data analysis and visualization. RokaiXplorer streamlines data processing, analysis, and visualization through an interactive online interface, making it accessible to researchers without specialized training in proteomics or data science. With its comprehensive suite of modules, RokaiXplorer facilitates phospho-proteomic analysis at the level of phosphosites, proteins, kinases, biological processes, and pathways. The tool offers functionalities such as data normalization, statistical testing, activity inference, pathway enrichment, subgroup analysis, automated report generation, and multiple visualizations, including volcano plots, bar plots, heat maps, and network views. As a unique feature, RokaiXplorer allows researchers to effortlessly deploy their own data browsers, enabling interactive sharing of research data and findings. Overall, RokaiXplorer fills an important gap in phospho-proteomic data analysis by providing the ability to comprehensively analyze data at multiple levels within a single application. Availability and implementation: Access RokaiXplorer at: http://explorer.rokai.io.

Exploring temporal and sex-linked dysregulation in Alzheimer disease phosphoproteome.

This study aims to characterize dysregulation of phosphorylation for the 5XFAD mouse model of Alzheimer disease (AD). Employing global phosphoproteome measurements, we analyze temporal (3, 6, and 9 months) and sex-dependent effects on mouse hippocampus tissue to unveil molecular signatures associated with AD initiation and progression. Our findings reveal consistent phosphorylation of known AD biomarkers APOE and GFAP in 5XFAD mice, alongside candidates BIG3, CLCN6, and STX7, suggesting their potential as biomarkers for AD pathology. In addition, we identify PDK1 as a significantly dysregulated kinase at 9 months in females, and the regulation of gap junction activity as a key pathway associated with Alzheimer disease across all time points. AD-Xplorer, the interactive browser of our dataset, enables exploration of AD-related changes in phosphorylation, protein expression, kinase activities, and pathways. AD-Xplorer aids in biomarker discovery and therapeutic target identification, emphasizing temporal and sex-specific nature of significant phosphoproteomic signatures. Available at: https://yilmazs.shinyapps.io/ADXplorer.

Prediction of Kinase-Substrate Associations Using The Functional Landscape of Kinases and Phosphorylation Sites.

Protein phosphorylation is a key post-translational modification that plays a central role in many cellular processes. With recent advances in biotechnology, thousands of phosphorylated sites can be identified and quantified in a given sample, enabling proteome-wide screening of cellular signaling. However, for most (> 90%) of the phosphorylation sites that are identified in these experiments, the kinase(s) that target these sites are unknown. To broadly utilize available structural, functional, evolutionary, and contextual information in predicting kinase-substrate associations (KSAs), we develop a network-based machine learning framework. Our framework integrates a multitude of data sources to characterize the landscape of functional relationships and associations among phosphosites and kinases. To construct a phosphosite-phosphosite association network, we use sequence similarity, shared biological pathways, co-evolution, co-occurrence, and co-phosphorylation of phosphosites across different biological states. To construct a kinase-kinase association network, we integrate protein-protein interactions, shared biological pathways, and membership in common kinase families. We use node embeddings computed from these heterogeneous networks to train machine learning models for predicting kinase-substrate associations. Our systematic computational experiments using the PhosphositePLUS database shows that the resulting algorithm, NetKSA, outperforms two state-of-the-art algorithms, including KinomeXplorer and LinkPhinder, in overall KSA prediction. By stratifying the ranking of kinases, NetKSA also enables annotation of phosphosites that are targeted by relatively less-studied kinases.Availability: The code and data are available at compbio.case.edu/NetKSA/.

Biologic Agents in Crohn's Patients Reduce CD4+ T Cells Activation and Are Inversely Related to Treg Cells.

Crohn's disease (CD) is a chronic inflammatory disease with a complex interface of broad factors. There are two main treatments for Chron's disease: biological therapy and nonbiological therapy. Biological agent therapy (e.g., anti-TNF) is the most frequently prescribed treatment; however, it is not universally accessible. In fact, in Brazil, many patients are only given the option of receiving nonbiological therapy. This approach prolongs the subsequent clinical relapse; however, this procedure could be implicated in the immune response and enhance disease severity. Our purpose was to assess the effects of different treatments on CD4+ T cells in a cohort of patients with Crohn's disease compared with healthy individuals. To examine the immune status in a Brazilian cohort, we analyzed CD4+ T cells, activation status, cytokine production, and Treg cells in blood of Crohn's patients. Patients that underwent biological therapy can recover the percentage of CD4+CD73+ T cells, decrease the CD4+ T cell activation/effector functions, and maintain the peripheral percentage of regulatory T cells. These results show that anti-TNF agents can improve CD4+ T cell subsets, thereby inducing Crohn's patients to relapse and remission rates.

Integrated systems approach defines the antiviral pathways conferring protection by the RV144 HIV vaccine.

The RV144 vaccine trial showed reduced risk of HIV-1 acquisition by 31.2%, although mechanisms that led to protection remain poorly understood. Here we identify transcriptional correlates for reduced HIV-1 acquisition after vaccination. We assess the transcriptomic profile of blood collected from 223 participants and 40 placebo recipients. Pathway-level analysis of HIV-1 negative vaccinees reveals that type I interferons that activate the IRF7 antiviral program and type II interferon-stimulated genes implicated in antigen-presentation are both associated with a reduced risk of HIV-1 acquisition. In contrast, genes upstream and downstream of NF-κB, mTORC1 and host genes required for viral infection are associated with an increased risk of HIV-1 acquisition among vaccinees and placebo recipients, defining a vaccine independent association with HIV-1 acquisition. Our transcriptomic analysis of RV144 trial samples identifies IRF7 as a mediator of protection and the activation of mTORC1 as a correlate of the risk of HIV-1 acquisition.