DSBSO-Based XL-MS Analysis of Breast Cancer PDX Tissues to Delineate Protein Interaction Network in Clinical Samples.

Protein-protein interactions (PPIs) are fundamental to understanding biological systems as protein complexes are the active molecular modules critical for carrying out cellular functions. Dysfunctional PPIs have been associated with various diseases including cancer. Systems-wide PPI analysis not only sheds light on pathological mechanisms, but also represents a paradigm in identifying potential therapeutic targets. In recent years, cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for defining endogenous PPIs of cellular networks. While proteome-wide studies have been performed in cell lysates, intact cells and tissues, applications of XL-MS in clinical samples have not been reported. In this study, we adopted a DSBSO-based in vivo XL-MS platform to map interaction landscapes from two breast cancer patient-derived xenograft (PDX) models. As a result, we have generated a PDX interaction network comprising 2,557 human proteins and identified interactions unique to breast cancer subtypes. Interestingly, most of the observed differences in PPIs correlated well with protein abundance changes determined by TMT-based proteome quantitation. Collectively, this work has demonstrated the feasibility of XL-MS analysis in clinical samples, and established an analytical workflow for tissue cross-linking that can be generalized for mapping PPIs from patient samples in the future to dissect disease-relevant cellular networks.

Protein interaction landscapes revealed by advanced in vivo cross-linking-mass spectrometry.

Defining protein-protein interactions (PPIs) in their native environment is crucial to understanding protein structure and function. Cross-linking-mass spectrometry (XL-MS) has proven effective in capturing PPIs in living cells; however, the proteome coverage remains limited. Here, we have developed a robust in vivo XL-MS platform to facilitate in-depth PPI mapping by integrating a multifunctional MS-cleavable cross-linker with sample preparation strategies and high-resolution MS. The advancement of click chemistry-based enrichment significantly enhanced the detection of cross-linked peptides for proteome-wide analyses. This platform enabled the identification of 13,904 unique lysine-lysine linkages from in vivo cross-linked HEK 293 cells, permitting construction of the largest in vivo PPI network to date, comprising 6,439 interactions among 2,484 proteins. These results allowed us to generate a highly detailed yet panoramic portrait of human interactomes associated with diverse cellular pathways. The strategy presented here signifies a technological advancement for in vivo PPI mapping at the systems level and can be generalized for charting protein interaction landscapes in any organisms.

Two-Dimensional Fractionation Method for Proteome-Wide Cross-Linking Mass Spectrometry Analysis.

Cross-linking mass spectrometry (XL-MS) is an emergent technology for studying protein-protein interactions (PPIs) and elucidating architectures of protein complexes. The development of various MS-cleavable cross-linkers has facilitated the identification of cross-linked peptides, enabling XL-MS studies at the systems level. However, the scope and depth of cellular networks revealed by current XL-MS technologies remain limited. Due to the inherently broad dynamic range and complexity of proteomes, interference from highly abundant proteins impedes the identification of low-abundance cross-linked peptides in complex samples. Thus, peptide enrichment prior to MS analysis is necessary to enhance cross-link identification for proteome-wide studies. Although chromatographic techniques including size exclusion (SEC) and strong cation exchange (SCX) have been successful in isolating cross-linked peptides, new fractionation methods are still needed to further improve the depth of PPI mapping. Here, we present a two-dimensional (2D) separation strategy by integrating peptide SEC with tip-based high pH reverse-phase (HpHt) fractionation to expand the coverage of proteome-wide XL-MS analyses. Combined with the MS-cleavable cross-linker DSSO, we have successfully mapped in vitro PPIs from HEK293 cell lysates with improved identification of cross-linked peptides compared to existing approaches. The method developed here is effective and can be generalized for cross-linking studies of complex samples.

Virus Bioresistor (VBR) for Detection of Bladder Cancer Marker DJ-1 in Urine at 10 pM in One Minute.

DJ-1, a 20.7 kDa protein, is overexpressed in people who have bladder cancer (BC). Its elevated concentration in urine allows it to serve as a marker for BC. However, no biosensor for the detection of DJ-1 has been demonstrated. Here, we describe a virus bioresistor (VBR) capable of detecting DJ-1 in urine at a concentration of 10 pM in 1 min. The VBR consists of a pair of millimeter-scale gold electrodes that measure the electrical impedance of an ultrathin (≈ 150-200 nm), two-layer polymeric channel. The top layer of this channel (90-105 nm in thickness) consists of an electrodeposited virus-PEDOT (PEDOT is poly(3,4-ethylenedioxythiophene)) composite containing embedded M13 virus particles that are engineered to recognize and bind to the target protein of interest, DJ-1. The bottom layer consists of spin-coated PEDOT-PSS (poly(styrenesulfonate)). Together, these two layers constitute a current divider. We demonstrate here that reducing the thickness of the bottom PEDOT-PSS layer increases its resistance and concentrates the resistance drop of the channel in the top virus-PEDOT layer, thereby increasing the sensitivity of the VBR and enabling the detection of DJ-1. Large signal amplitudes coupled with the inherent simplicity of the VBR sensor design result in high signal-to-noise (S/N > 100) and excellent sensor-to-sensor reproducibility characterized by coefficients of variation in the range of 3-7% across the DJ-1 binding curve down to a concentration of 30 pM, near the 10 pM limit of detection (LOD), encompassing four orders of magnitude in concentration.

Investigation of Humidity Dependent Surface Morphology and Proton Conduction in Multi-Acid Side Chain Membranes by Conductive Probe Atomic Force Microscopy.

In this report, we employ phase-contrast tapping mode and conductive probe atomic force microscopy (cp-AFM) as tools to investigate the nanoscale morphology and proton conductance of a 3M perfluoro-imide acid (PFIA) membrane (625 EW) over a large range of relative humidity (3-95% RH). As a point of comparison, we also investigate 3M perfluorosulfonic acid (PFSA) (825 EW) and Nafion 212. With AFM, we assess the membrane's water retention and mechanical stability at low RH and high RH, respectively. Cp-AFM allows us to spatially resolve the hydrophilic and electrochemically active domains under a similar set of conditions and observe directly the ties between membrane morphology and proton conductance. From our data, we are able to correlate the improved water retention indicated by the size of the hydrophilic domains with the proton conductance in the PFIA membrane at elevated temperature and compare the result with that observed for the PFSA and Nafion. At high RH conditions, we see evidence of a nearly continuous hydrophilic phase, which indicates a high degree of swelling.

ChemSem: an extensible and scalable RSS-based seminar alerting system for scientific collaboration.

A seminar announcement system based on the extensive use of XML-based data structures, CML/MathML for carrying more domain-specific molecular content, and open source software components is described. The output is a resource description framework (RDF) site summary (RSS) feed, which potentially carries many advantages over conventional announcement mechanisms, including the ability to aggregate and then sort multiple and diverse RSS feeds on the basis of declared metadata and to feed into RDF-based mechanisms for establishing links between different subject areas.