Cells and extracellular matrix (ECM) are mutually interdependent: cells guide self-assembly of ECM precursors, and the resulting ECM architecture supports and instructs cells. Though bidirectional signaling between ECM and cells is fundamental to cell biology, it is challenging to gain high-resolution structural information on cellular responses to the matrix microenvironment. Here we used cryo-scanning transmission electron tomography (CSTET) to reveal the nanometer- to micron-scale organization of major fibroblast ECM components in a native-like context, while simultaneously visualizing internal cell ultrastructure including organelles and cytoskeleton. In addition to extending current models for collagen VI fibril organization, three-dimensional views of thick cell regions and surrounding matrix showed how ECM networks impact the structures and dynamics of intracellular organelles and how cells remodel ECM. Collagen VI and fibronectin were seen to distribute in fundamentally different ways in the cell microenvironment and perform distinct roles in supporting and interacting with cells. This work demonstrates that CSTET provides a new perspective for the study of ECM in cell biology, highlighting labeled extracellular elements against a backdrop of unlabeled but morphologically identifiable cellular features with nanometer resolution detail.

Real-time database searching allows for simpler and automated proteomics workflows as it eliminates technical bottlenecks in high-throughput experiments. Most importantly, it enables results-dependent acquisition (RDA), where search results can be used to guide data acquisition during acquisition. This is especially beneficial for glycoproteomics since the wide range of physicochemical properties of glycopeptides lead to a wide range of optimal acquisition parameters. We established here the GlycoPaSER prototype by extending the Parallel Search Engine in Real-time (PaSER) functionality for real-time glycopeptide identification from fragmentation spectra. Glycopeptide fragmentation spectra were decomposed into peptide and glycan moiety spectra using common N-glycan fragments. Each moiety was subsequently identified by a specialized algorithm running in real-time. GlycoPaSER can keep up with the rate of data acquisition for real-time analysis with similar performance to other glycoproteomics software and produces results that are in line with the literature reference data. The GlycoPaSER prototype presented here provides the first proof-of-concept for real-time glycopeptide identification that unlocks the future development of RDA technology to transcend data acquisition.

Human Leukocyte Antigen (HLA) complexes are critical cell-surface protein assemblies that facilitate T-cell surveillance of almost all cell types in the body. While T-cell receptor binding to HLA class I and class II complexes is well-described with detailed structural information, the nature of cis HLA interactions within the plasma membrane of the surveyed cells remains to be better characterized, as protein-protein interactions in the membrane environment are technically challenging to profile. Here we performed extracellular chemical crosslinking on intact antigen presenting cells to specifically elucidate protein-protein interactions present in the external plasma membrane. We found that the crosslink dataset was dominated by inter- and intra-protein crosslinks involving HLA molecules, which enabled not only the construction of an HLA-centric plasma membrane protein interaction map, but also revealed multiple modes of HLA class I - HLA class II interactions with further structural modeling based on crosslinker distance restraints. Collectively, our data demonstrate that HLA molecules colocalize and can be densely packed on the plasma membrane.

The two major proteins involved in Alzheimer’s disease (AD) are the amyloid precursor protein (APP) and Tau. Here, we demonstrate that these two proteins can bind to each other. Four possible peptides APP1 (390–412), APP2 (713–730), Tau1 (19–34) and Tau2 (331–348), were predicted to be involved in this interaction, with actual binding confirmed for APP1 and Tau1. In vivo studies were performed in an Alzheimer Disease animal model—APP double transgenic (Tg) 5xFAD—as well as in 5xFAD crossed with Tau transgenic 5xFADXTau (FT), which exhibit declined cognitive reduction at four months of age. Nasal administration of APP1 and Tau1 mixture, three times a week for four or five months, reduced amyloid plaque burden as well as the level of soluble Aβ 1–42 in the brain. The treatment prevented the deterioration of cognitive functions when initiated at the age of three months, before cognitive deficiency was evident, and also at the age of six months, when such deficiencies are already observed, leading to a full regain of cognitive function.

Background/Objectives: Multiple Myeloma (MM) is a hematologic malignancy caused by clonally expanded plasma cells that produce a monoclonal immunoglobulin (M-protein), a personalized biomarker. Recently, we developed an ultra-sensitive mass spectrometry method to quantify minimal residual disease (MS-MRD) by targeting unique M-protein peptides. Therapeutic antibodies (t-Abs), key in MM treatment, often lead to deep and long-lasting responses. However, t-Abs can significantly decrease the total polyclonal immunoglobulin (Ig) levels which require supplemental IgG infusion. Here, we demonstrate the simultaneous monitoring of M-proteins, t-Abs, and polyclonal Ig-titers using an untargeted mass spectrometry assay, offering a comprehensive view of therapy response. Methods: Sera collected between 2013 and 2024 from four patients and cerebrospinal fluid (CSF) from one patient who received various t-Abs were analyzed with MS-MRD. M-protein sequences were obtained with a multi-enzyme de novo protein sequencing approach. Unique peptides for M-proteins and t-Abs were selected based on linearity, sensitivity, and slope coefficient in serial dilutions. Ig constant regions were monitored using isotype-specific peptides. Results: The MS-MRD multiplex analysis provided detailed information on drug concentrations and therapy response kinetics. For example, in two patients with refractory disease over five lines of therapy, the MS-MRD analysis showed that the deepest responses were achieved with bispecific t-Ab (teclistamab) treatment. M-protein and t-Ab were also detectable in the CSF of one patient with MS-MRD. Conclusions: This proof-of-concept study shows that the multiplex monitoring of the M-protein, any t-Ab combination, and all Ig-isotypes within one mass spectrometry run is feasible and provides unique insight into therapy response kinetics.

Real-time database searching allows for simpler and automated proteomics workflows as it eliminates technical bottlenecks in high throughput experiments. Most importantly, it enables results dependent acquisition (RDA) where search results can be used to guide data acquisition during acquisition. This is especially beneficial for glycoproteomics since the wide range of physicochemical properties of glycopeptides lead to a wide range of optimal acquisition parameters. We established here the GlycoPaSER prototype by extending the Parallel Search Engine in Real-time (PaSER) functionality for real-time glycopeptide identification from fragmentation spectra. Glycopeptide fragmentation spectra were decomposed into peptide- and glycan-moiety spectra using common N-glycan fragments. Each moiety was subsequently identified by a specialized algorithm running in real-time. GlycoPaSER can keep up with the rate of data acquisition for real-time analysis with similar performance to other glycoproteomics software and produces results that are in line with literature reference data. The GlycoPaSER prototype presented here provides the first proof-of-concept for real-time glycopeptide identification that unlocks future development of RDA technology to transcend data acquisition.