Biology subjects

Soleimany, A. P.

Publications and source records attributed to Soleimany, A. P..

5 recordsLinked to original sources

bioRxiv2022

Protease Activity Analysis: A Toolkit for Analyzing Enzyme Activity Data

Analyzing the activity of proteases and their substrates is critical to defining the biological functions of these enzymes and to designing new diagnostics and therapeutics that target protease dysregulation in disease. While a wide range of databases and algorithms have been created to better predict protease cleavage sites, there is a dearth of computational tools to automate analysis of in vitro and in vivo protease assays. This necessitates individual researchers to develop their own analytical pipelines, resulting in a lack of standardization across the field. To facilitate protease research, here we present Protease Activity Analysis (PAA), a toolkit for the preprocessing, visualization, machine learning analysis, and querying of protease activity datasets. PAA leverages a Python-based object-oriented implementation that provides a modular framework for streamlined analysis across three major components. First, PAA provides a facile framework to query datasets of synthetic peptide substrates and their cleavage susceptibilities across a diverse set of proteases. To complement the database functionality, PAA also includes tools for the automated analysis and visualization of user-input enzyme-substrate activity measurements generated through in vitro screens against synthetic peptide substrates. Finally, PAA can supports a set of modular machine learning functions to analyze in vivo protease activity signatures that are generated by activity-based sensors. Overall, PAA offers the protease community a breadth of computational tools to streamline research, taking a step towards standardizing data analysis across the field and in chemical biology and biochemistry at large.

bioinformatics↗

bioRxiv2021

Spatially regulated protease activity in lymph nodes renders B cell follicles a sanctuary for retention of intact antigens

The structural integrity of vaccine antigens is critical, as antigen degradation in vivo could eliminate neutralizing epitopes and create competing B cell responses against irrelevant breakdown products. Using FRET imaging and imaging zymography, we found that protease activity and antigen breakdown are spatially heterogeneous in lymph nodes. Following protein immunization, antigens are rapidly degraded in the subcapsular sinus, paracortex, and interfollicular regions of the tissue. By contrast, the follicles and follicular dendritic cell (FDC) networks exhibit low protease activity and antigen degradation rates. Immunization regimens targeting antigen rapidly to FDCs led to germinal centers (GCs) where responses to intact antigen were highly dominant, while traditional bolus immunizations led to weaker GC responses where more GC B cells bound to breakdown products than intact antigen. Thus, spatially-compartmentalized antigen proteolysis impacts humoral immunity and can be exploited to enhance vaccine-induced production of antibody responses against key pathogen structural epitopes.

immunology↗

bioRxiv2021

Multiscale profiling of enzyme activity in cancer

Diverse processes in cancer are mediated by enzymes, which most proximally exert their function through their activity. Methods to quantify enzyme activity, rather than just expression, are therefore critical to our ability to understand the pathological roles of enzymes in cancer and to harness this class of biomolecules as diagnostic and therapeutic targets. Here we present an integrated set of methods for measuring specific enzyme activities across the organism, tissue, and cellular levels, which we unify into a methodological hierarchy to facilitate biological discovery. We focus on proteases for method development and validate our approach through the study of tumor progression and treatment response in an autochthonous model of Alk-mutant lung cancer. To quantitatively measure activity dynamics over time, we engineered multiplexed, peptide-based nanosensors to query protease activity in vivo. Machine learning analysis of sensor measurements revealed dramatic protease dysregulation in lung cancer, including significantly enhanced proteolytic cleavage of one peptide, S1 (Padj < 0.0001), which returned to healthy levels within three days after initiation of targeted therapy. Next, to link these organism-level observations to the in situ context, we established a multiplexed assay for on-tissue localization of enzyme activity and pinpointed S1 cleavage to endothelial cells and pericytes of the tumor vasculature. Lastly, to directly link enzyme activity measurements to cellular phenotype, we designed a high-throughput method to isolate and characterize proteolytically active cells, uncovering profound upregulation of pro-angiogenic transcriptional programs in S1-positive cells. Together, these methods allowed us to discover that protease production by angiogenic vasculature responds rapidly to targeted therapy against oncogene-addicted tumor cells, identifying a highly dynamic interplay between tumor cells and their microenvironment. This work provides a generalizable framework to functionally characterize enzyme activity in cancer.

bioengineering↗

bioRxiv2020

Activatable zymography probes enable in situ localization of protease dysregulation in cancer

Recent years have seen the emergence of conditionally activated diagnostics and therapeutics that leverage protease-cleavable peptide linkers to enhance their specificity for cancer. However, due to a lack of methods to measure and localize protease activity directly within the tissue microenvironment, the design of protease-activated agents has been necessarily empirical, yielding suboptimal results when translated to patients. To address the need for spatially resolve d protease activity profiling in cancer, we developed a new class of in situ probes that can be applied to fresh-frozen tissue sections in a manner analogous to immunofluorescence staining. These activatable zymography probes (AZPs) detected dysregulated protease activity in human prostate cancer biopsy samples, enabling disease classification. We then leveraged AZPs within a generalizable framework to design conditional cancer diagnostics and therapeutics, and demonstrated the power of this approach in the Hi-Myc mouse model of prostate cancer, which models features of early pathogenesis. Multiplexed screening against barcoded substrates yielded a peptide, S16, that was robustly and specifically cleaved by tumor-associated metalloproteinases in the Hi-Myc model. In situ labeling with an AZP incorporating S16 revealed a potential role of metalloproteinase dysregulation in proliferative, pre-malignant Hi-Myc prostatic glands. Last, we incorporated S16 into an in vivo imaging probe that, after systemic administration, perfectly classified diseased and healthy prostates, supporting the relevance of ex vivo activity assays to in vivo translation. We envision AZPs will enable new insights into the biology of protease dysregulation in cancer and accelerate the development of conditional diagnostics and therapeutics for multiple cancer types.

bioengineering↗

bioRxiv2019

Genetic encoding of targeted MRI contrast agents for in vivo tumor imaging

Tumor-selective contrast agents have the potential to aid in the diagnosis and treatment of cancer using noninvasive imaging modalities such as magnetic resonance imaging (MRI). Such contrast agents can consist of magnetic nanoparticles incorporating functionalities that respond to cues specific to tumor environments. Genetically engineering magnetotactic bacteria to display peptides has been investigated as a means to produce contrast agents that combine the robust image contrast effects of magnetosomes with transgenic targeting peptides displayed on their surface. This work reports the first use of magnetic nanoparticles that display genetically-encoded pH low insertion peptide (pHLIP), a long peptide intended to enhance MRI contrast by targeting the extracellular acidity associated with the tumors. To demonstrate the modularity of this versatile platform to incorporate diverse targeting ligands by genetic engineering, we also incorporated the cyclic v integrin-binding peptide iRGD into separate magnetosomes. Specifically, we investigate their potential for enhanced binding and tumor imaging both in vitro and in vivo. Our experiments indicate that these tailored magnetosomes retain their magnetic properties, making them well-suited as T2 contrast agents, while exhibiting increased binding compared to wild-type magnetosomes.

synthetic biology↗