The fundamentals of how protein–protein/RNA/DNA interactions influence the structures and functions of the workhorses from the cells have been well documented in the 20th century. A diverse set of methods exist to determine such interactions between different components, particularly, the mass spectrometry (MS) methods, with its advanced instrumentation, has become a significant approach to analyze a diverse range of biomolecules, as well as bring insights to their biomolecular processes. This review highlights the principal role of chemistry in MS-based structural proteomics approaches, with a particular focus on the chemical cross-linking of protein–protein/DNA/RNA complexes. In addition, we discuss different methods to prepare the cross-linked samples for MS analysis and tools to identify cross-linked peptides. Cross-linking mass spectrometry (CLMS) holds promise to identify interaction sites in larger and more complex biological systems. The typical CLMS workflow allows for the measurement of the proximity in three-dimensional space of amino acids, identifying proteins in direct contact with DNA or RNA, and it provides information on the folds of proteins as well as their topology in the complexes. Principal CLMS applications, its notable successes, as well as common pipelines that bridge proteomics, molecular biology, structural systems biology, and interactomics are outlined.

Robotically assisted proteomics provides insights into the regulation of multiple proteins achieving excellent spatial resolution. However, developing an effective method for spatially resolved quantitative proteomics of formalin fixed paraffin embedded tissue (FFPE) in an accessible and economical manner remains challenging. We introduce non-robotic In-insert FFPE proteomics approach, combining glass insert FFPE tissue processing with spatial quantitative data-independent mass spectrometry (DIA). In-insert approach identifies 450 proteins from a 5 µm thick breast FFPE tissue voxel with 50 µm lateral dimensions covering several tens of cells. Furthermore, In-insert approach associated a keratin series and moesin (MOES) with prolactin-induced protein (PIP) indicating their prolactin and/or estrogen regulation. Our data suggest that PIP is a spatial biomarker for hormonally triggered cytoskeletal remodeling, potentially useful for screening hormonally affected hotspots in breast tissue. In-insert proteomics represents an alternative FFPE processing method, requiring minimal laboratory equipment and skills to generate spatial proteotype repositories from FFPE tissue.

The IFITM restriction factors play a role in cancer cell progression through undefined mechanisms. We investigate new protein–protein interactions for IFITM1/3 in the context of cancer that would shed some light on how IFITM1/3 attenuate the expression of targeted proteins such as HLA-B. SBP-tagged IFITM1 protein was used to identify an association of IFITM1 protein with the SRSF1 splicing factor and transporter of mRNA to the ribosome. Using in situ proximity ligation assays, we confirmed a predominant cytosolic protein–protein association for SRSF1 and IFITM1/3. Accordingly, IFITM1/3 interacted with HLA-B mRNA in response to IFNγ stimulation using RNA–protein proximity ligation assays. In addition, RT-qPCR assays in IFITM1/IFITM3 null cells and wt-SiHa cells indicated that HLA-B gene expression at the mRNA level does not account for lowered HLA-B protein synthesis in response to IFNγ. Complementary, shotgun RNA sequencing did not show major transcript differences between IFITM1/IFITM3 null cells and wt-SiHa cells. Furthermore, ribosome profiling using sucrose gradient sedimentation identified a reduction in 80S ribosomal fraction an IFITM1/IFITM3 null cells compared to wild type. It was partially reverted by IFITM1/3 complementation. Our data link IFITM1/3 proteins to HLA-B mRNA and SRSF1 and, all together, our results begin to elucidate how IFITM1/3 catalyze the synthesis of target proteins. IFITMs are widely studied for their role in inhibiting viruses, and multiple studies have associated IFITMs with cancer progression. Our study has identified new proteins associated with IFITMs which support their role in mediating protein expression; a pivotal function that is highly relevant for viral infection and cancer progression. Our results suggest that IFITM1/3 affect the expression of targeted proteins; among them, we identified HLA-B. Changes in HLA-B expression could impact the presentation and recognition of oncogenic antigens on the cell surface by cytotoxic T cells and, ultimately, limit tumor cell eradication. In addition, the role of IFITMs in mediating protein abundance is relevant, as it has the potential for regulating the expression of viral and oncogenic proteins.

Sample preparation is a key step in proteomics, however there is no consensus in the community about the standard method for preparation of proteins from clinical samples like tissues or biofluids. In this chapter, we will discuss some important steps in sample preparation used for bottom-up proteome profiling with mass spectrometry (MS). Specifically, tissues, which are an important source of biological information, are of interest because of their availability. Tissues are most often stored as fresh frozen (FF) or formalin-fixed paraffin-embedded (FFPE). While FF tissues are more readily available, paraffin embedding has historically been routinely used for tissue preservation. However, formaldehyde induced crosslinks during FFPE tissue preservation present a challenge to the protocols used for protein retrieval. Moreover, in our view, an important aspect to consider is also the amount of material available at the start of a protocol since this is directly related to the choice of protocol in order to minimize sample loss and maximize detection of peptides by MS. This “MS sensitivity” is of special importance when working with patient samples that are unique and often available in limited amounts making optimization of methods to analyze the proteins therein important given that their molecular information can be used in a patients’ diagnosis and treatment.

Melanoma is an aggressive cancer with rising incidence and high mortality rates, largely due to chemotherapy resistance and molecular dysregulation. Nanotechnology, particularly silver nanoparticles (AgNPs), has emerged as a promising therapeutic avenue because of the nanoparticles’ ability to induce oxidative stress and apoptosis in cancer cells. However, conventional colloidal AgNPs lack selectivity, often causing significant damage to healthy cells. In this study, we introduce a green synthesis of AgNPs using plant extracts, providing an eco-friendly alternative with improved antitumor selectivity compared to traditional colloidal AgNPs. Leveraging label-free Data-Independent Acquisition/Sequential Window Acquisition of All Theoretical Mass Spectrometry (DIA/SWATH MS) quantitative proteomics, we investigated the antitumor effects of green-synthesized versus traditional AgNPs on A375 melanoma cells at 24 and 48 h. Our findings reveal that green AgNPs selectively reduced melanoma cell viability while sparing healthy keratinocytes (HaCaT), a benefit not observed with colloidal AgNPs. Proteomic analysis highlighted that green AgNPs significantly downregulated oncogenes, enhanced carbohydrate metabolism, and disrupted copper homeostasis in melanoma cells. This marks the first study to explore the differential effects of green and traditional AgNPs on melanoma using an integrated proteomic approach, underscoring the molecular potential of green AgNPs as a targeted and sustainable option for cancer therapy.

The neuroprotective E3-ubiquitin ligase CHIP is linked to healthy aging. Here, we present a protocol using a patient-derived iPSC line with a triplication of the α-synuclein gene to produce gene-edited cells isogenic for CHIP. We describe iPSC differentiation into cortical neurons and their identity validation. We then detail mass spectrometry-based approaches (SWATH-MS) to identify dominant changes in the steady state proteome generated by loss of CHIP function. This protocol can be adapted to other proteins that impact proteostasis in neurons.