Marija Veličković

Identification of tissue-region-specific changes in glycosylation is crucial for understanding the pathogenesis of kidney diseases, yet it remains a great challenge. We developed a workflow that combines matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) data with AI-based digital pathology annotations of kidney functional tissue units (FTUs) to profile N-glycan distributions within biopsy tissues. This approach can generate molecular-level data relevant to diverse pathological outcomes, thereby aiding in the elucidation of disease mechanisms. As a proof-of-concept, we demonstrate that this AI-based digital pathology approach to MALDI data segmentation enables the detection and differentiation of N-glycosylation within FTUs of healthy kidney tissue. We then elucidated differences in N-glycosylation between the diseased kidney tissue samples from patients with different diagnoses. Sialic acid N-glycans, which have been linked to various kidney diseases, displayed enrichment in the glomeruli and tubules of tissues from patients diagnosed with diabetic kidney disease (DKD), whereas they were enriched in the tubules and arteries from patients with acute kidney injury (AKI), in comparison to healthy tissue. Furthermore, we found that polylactosamine N-glycans were enriched only in the AKI samples, indicating their potential roles in tubular injury and inflammation. This workflow has the potential to bridge the gap between region-specific glycosylation and its implications on FTUs in diseases, paving the way for targeted molecular imaging studies in the kidney and other tissues.

Bulk proteomics has been demonstrated to differentiate subpopulations based on molecular phenotypes within bacterial colonies, yet advanced analyses by mass spectrometry imaging (MSI) hold even greater promise for the future. This technology can enable high-throughput spatial phenotyping that can directly visualize distinct components of various biomolecular mechanisms with high mass resolving power in high spatial resolution analyses. Here, we applied MSI for intact protein imaging directly from thin cross sections of a biofilm of Bacillus subtilis and after minimal preparation we detected more than 285 unique isotopic envelopes corresponding to unique proteoforms. We paired our MSI analyses with bulk top-down proteomics (TDP) to form extensive experimental libraries, which provided us with high confidence MSI annotations based upon isotopic matching to validated post-translational modifications (PTMs) and truncations. This joint application of MSI and TDP allowed us to describe the microscal e spatial proteomic landscape within the B. subtilis biofilm. This study further demonstrated the feasibility of detecting differentiated subpopulations of cells through the identification of proteoforms of cannibalistic protein toxins as well as those involved in active sporulation to highly localized areas within the central and outermost periphery of the biofilm. GRAPHICAL

Leaf-cutter ant fungal gardens are a living library of bioeconomy solutions, where the mutualist fungus Leucoagaricus gongylophorus drives lignocellulose degradation and conversion into valuable bioproducts. However, these gardens are vulnerable to infection by the specialized pathogen Escovopsis weberi, which disrupts garden stability. Despite their ecological importance, the metabolic mechanisms underlying fungal–fungal competition and community-level responses to infection remain poorly understood. To address this gap, we experimentally infected six fungal garden consortia with E. weberi, establishing an infection gradient within each consortium, which we then systematically analyzed using a multi-omics approach. Metabolomic profiling revealed infection-induced alterations in metabolite abundance, while metaproteomic analysis identified fungal-specific shifts in protein levels across a spatiotemporal scale. The integration of multi-omics datasets across all fungal garden consortia provided a comprehensive view of the underlying pathways, revealing that the pathogenic fungus exploits nutrient supplies derived from lignocellulose degradation by native fungi. Reconstruction of active pathways enabled us to trace nutrient flow and map taxon-specific metabolic shifts in response to infection. Specifically, a distinct switch from lysine synthesis by native fungi to lysine catabolism orchestrated by pathogenic fungi. These findings offer a system-level perspective of the molecular alterations driving competitive interactions between native and pathogenic species within the fungal garden consortium. This study not only highlights the power of multi-omics approaches in unraveling the complexity of microbial consortia across ecological scales but also provides an integrated road map to efficiently harness microbiome data for deeper insights into microbial interactions and community responses to perturbations.

Spatially resolved mass spectrometry (MS)-based multiomics workflows are becoming more utilized for revealing the complex biology that occurs within tissues. However, these approaches commonly require multiple independent tissue sections to analyze the metabolite and protein compositions of these samples. This poses a significant challenge in preserving cell- or region-specific molecular fidelity, as variations between tissue sections can compromise the accurate correlation of molecular data. Here, we developed workflows for comprehensive multiomics profiling from a single tissue section (STS) using different MS modalities. We enhanced the functionality of an electrically insulated substrate by employing metal-assisted approaches that enabled both MS-based untargeted spatial metabolomics and proteomics from STS. This allowed metabolite imaging using matrix-assisted laser desorption/ionization-MS imaging (MALDI-MSI), without compromising it for subsequent proteome profiling with laser capture microdissection (LCM)-based technology. Specifically, implementing copper tape as a backing for polyethylene naphthalate (PEN) slides enabled the detection of >140 metabolites across a poplar root tissue section using MALDI-trapped ion mobility spectrometry time-of-flight (timsTOF)-MS. Afterward, we detected 6571 unique proteins from two distinct root regions by leveraging LCM technology coupled to our microdroplet based sample preparation approach. We also developed an alternative workflow utilizing gold-coated PEN substrates for imaging with MALDI-Fourier-transform ion cyclotron resonance (FTICR)-MS, which permitted the profiling of >170 metabolites and the identification of 6542 unique proteins across a single poplar root tissue section. These results were comparable to using each omics analysis independently. These approaches offer new opportunities for high-resolution molecular profiling of multiple omics levels across biological tissues.

The Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging. Using healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1–74) of ubiquitin within cortical regions. We developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) while discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.

The placenta is a complex and heterogeneous organ that links the mother and fetus, playing a crucial role in nourishing and protecting the fetus throughout pregnancy. Integrative spatial multi-omics approaches can provide a systems-level understanding of molecular changes underlying the mechanisms leading to the histological variations of the placenta during healthy pregnancy and pregnancy complications. Herein, we advance our metabolome-informed proteome imaging (MIPI) workflow to include lipidomic imaging, while also expanding the molecular coverage of metabolomic imaging by incorporating on-tissue chemical derivatization (OTCD). The improved MIPI workflow advances biomedical investigations by leveraging state-of-the-art molecular imaging technologies. Lipidome imaging identifies molecular differences between two morphologically distinct compartments of a placental villous functional unit, syncytiotrophoblast (STB) and villous core. Next, our advanced metabolome imaging maps villous functional units with enriched metabolomic activities related to steroid and lipid metabolism, outlining distinct molecular distributions across morphologically different villous compartments. Complementary proteome imaging on these villous functional units reveals a plethora of fatty acid- and steroid-related enzymes uniquely distributed in STB and villous core compartments. Integration across our advanced MIPI imaging modalities enables the reconstruction of active biological pathways of molecular synthesis and maternal-fetal signaling across morphologically distinct placental villous compartments with micrometer-scale resolution.

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures tissue heterogeneity, precluding proteome mapping of tissue microenvironment. Here we report an integrated wet collection of single microscale tissue voxels and Surfactant-assisted One-Pot voxel processing method termed wcSOP for robust label-free single voxel proteomics. wcSOP capitalizes on buffer droplet-assisted wet collection of single voxels dissected by LCM to the tube cap and SOP voxel processing in the same collection cap. This method enables reproducible, label-free quantification of approximately 900 and 4600 proteins for single voxels at 20 µm × 20 µm × 10 µm (~1 cell region) and 200 µm × 200 µm × 10 µm (~100 cell region) from fresh frozen human spleen tissue, respectively. It can reveal spatially resolved protein signatures and region-specific signaling pathways. Furthermore, wcSOP-MS is demonstrated to be broadly applicable for OCT-embedded and FFPE human archived tissues as well as for small-scale 2D proteome mapping of tissues at high spatial resolutions. wcSOP-MS may pave the way for routine robust single voxel proteomics and spatial proteomics.

RATIONALE Universally, the most common method of embedding dissected or resected fresh frozen (FF) tissues is within optimal cutting temperature (OCT) media. Unfortunately, OCT is not ideal for mass spectrometry (MS) assays. The media perfuses through tissues, resulting in persistent polymer contamination causing issues for sensitive analyses. Complete removal of all OCT media background would enable techniques such as MS imaging (MSI) to be bridged to clinically relevant samples stored in biobanks which possess extensive medical histories. Even though methods have been outlined for spatial lipidomics and proteomics, many still avoid these tissues despite vast potential for biological discoveries applying MS or MSI. METHODS Reference FF human pancreas was prepared within OCT media and cryosectioned for matrix-assisted laser desorption/ionization (MALDI)-MSI. Sample preparation protocols using aqueous ammonium formate for spatial lipidomics, and a variety of solutions for fixation, delipidation, and salt removal enabled spatial proteomics as well. MSI was performed on a UHMR HF Orbitrap MS detected broad classes of lipids and intact proteins, enabling an assessment of polymer perfusion and signal delocalization over a broad mass range to evaluate any deleterious artifacts. RESULTS We observe lower polymer contamination from OCT tissues with ammonium formate washes as expected, with several caveats. This was most effective in negative ion mode, where in tandem with the boosted lipid signal positive results were achieved for phospholipids (600-900 Da) and higher mass lipids (>1250 Da). Positive ion mode analyses can be completed for phospholipids, but the condensation of alkali adducts to protonated forms not only increased lipid signals, but also increased signals of larger, persistent PEG oligomers (>1250 Da) which were not previously reported. Even with extensive tissue washing completing a spatial proteomics protocol, the removal of all remnant artifacts of OCT media was not feasible. CONCLUSIONS The finding of these persistent remnant polymers from the OCT embedding process has several consequences for MSI, directly effecting primary performance of the MALDI source and lipid and protein analyses. This does not mean OCT tissues should not be or cannot be used for spatial omics by MSI, but several quality control and quality assurance measures should be implemented, and we discuss paths forward and several considerations.

Most of Earth’s trees rely on critical soil nutrients that ectomycorrhizal fungi (EcMF) liberate and provide, and all of Earth’s land plants associate with bacteria that help them survive in nature. Yet, our understanding of how the presence of EcMF modifies soil bacterial communities, soil food webs, and root chemistry requires direct experimental evidence to comprehend the effects that EcMF may generate in the belowground plant microbiome. To this end, we grew Pinus muricata plants in soils that were either inoculated with EcMF and native forest bacterial communities or only native bacterial communities. We then profiled the soil bacterial communities, applied metabolomics and lipidomics, and linked omics data sets to understand how the presence of EcMF modifies belowground biogeochemistry, bacterial community structure, and their functional potential. We found that the presence of EcMF (i) enriches soil bacteria linked to enhanced plant growth in nature, (ii) alters the quantity and composition of lipid and non-lipid soil metabolites, and (iii) modifies plant root chemistry toward pathogen suppression, enzymatic conservation, and reactive oxygen species scavenging. Using this multi-omic approach, we therefore show that this widespread fungal symbiosis may be a common factor for structuring soil food webs. IMPORTANCE: Understanding how soil microbes interact with one another and their host plant will help us combat the negative effects that climate change has on terrestrial ecosystems. Unfortunately, we lack a clear understanding of how the presence of ectomycorrhizal fungi (EcMF)—one of the most dominant soil microbial groups on Earth—shapes belowground organic resources and the composition of bacterial communities. To address this knowledge gap, we profiled lipid and non-lipid metabolites in soils and plant roots, characterized soil bacterial communities, and compared soils amended either with or without EcMF. Our results show that the presence of EcMF changes soil organic resource availability, impacts the proliferation of different bacterial communities (in terms of both type and potential function), and primes plant root chemistry for pathogen suppression and energy conservation. Our findings therefore provide much-needed insight into how two of the most dominant soil microbial groups interact with one another and with their host plant.

Key Points: Multiomics performed on diabetic kidney disease biopsies revealed five N-glycan signatures of sclerotic glomeruli that significantly differed compared with healthy glomeruli. Integrative spatial glycomics, proteomics, and transcriptomics revealed protein N-glycosylation characteristic of sclerotic glomeruli in diabetic kidney disease. Background: Diabetes is expected to directly affect renal glycosylation; yet to date, there has not been a comprehensive evaluation of alterations in N-glycan composition in the glomeruli of patients with diabetic kidney disease (DKD). Methods: We used untargeted mass spectrometry imaging to identify N-glycan structures in healthy and sclerotic glomeruli in formalin-fixed paraffin-embedded sections from needle biopsies of five patients with DKD and three healthy kidney samples. Regional proteomics was performed on glomeruli from additional biopsies from the same patients to compare the abundances of enzymes involved in glycosylation. Secondary analysis of single-nucleus RNA sequencing (snRNAseq) data were used to inform on transcript levels of glycosylation machinery in different cell types and states. Results: We detected 120 N-glycans, and among them, we identified 12 of these protein post-translated modifications that were significantly increased in glomeruli. All glomeruli-specific N-glycans contained an N-acetyllactosamine epitope. Five N-glycan structures were highly discriminant between sclerotic and healthy glomeruli. Sclerotic glomeruli had an additional set of glycans lacking fucose linked to their core, and they did not show tetra-antennary structures that were common in healthy glomeruli. Orthogonal omics analyses revealed lower protein abundance and lower gene expression involved in synthesizing fucosylated and branched N-glycans in sclerotic podocytes. In snRNAseq and regional proteomics analyses, we observed that genes and/or proteins involved in sialylation and N-acetyllactosamine synthesis were also downregulated in DKD glomeruli, but this alteration remained undetectable by our spatial N-glycomics assay. Conclusions: Integrative spatial glycomics, proteomics, and transcriptomics revealed protein N-glycosylation characteristic of sclerotic glomeruli in DKD.