Ectomycorrhizal fungi alter soil food webs and the functional potential of bacterial communities.

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.IMPORTANCEUnderstanding 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.

Spatial top-down proteomics for the functional characterization of human kidney.

Background: 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. Results: 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. Conclusions: We developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Where 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) where 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.

Mapping microhabitats of lignocellulose decomposition by a microbial consortium.

The leaf-cutter ant fungal garden ecosystem is a naturally evolved model system for efficient plant biomass degradation. Degradation processes mediated by the symbiotic fungus Leucoagaricus gongylophorus are difficult to characterize due to dynamic metabolisms and spatial complexity of the system. Herein, we performed microscale imaging across 12-µm-thick adjacent sections of Atta cephalotes fungal gardens and applied a metabolome-informed proteome imaging approach to map lignin degradation. This approach combines two spatial multiomics mass spectrometry modalities that enabled us to visualize colocalized metabolites and proteins across and through the fungal garden. Spatially profiled metabolites revealed an accumulation of lignin-related products, outlining morphologically unique lignin microhabitats. Metaproteomic analyses of these microhabitats revealed carbohydrate-degrading enzymes, indicating a prominent fungal role in lignocellulose decomposition. Integration of metabolome-informed proteome imaging data provides a comprehensive view of underlying biological pathways to inform our understanding of metabolic fungal pathways in plant matter degradation within the micrometer-scale environment.

Robust collection and processing for label-free single voxel proteomics.

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 important tissue heterogeneity, which make it impossible for proteome mapping of tissue microenvironment. Here we report an integrated wet collection of single tissue voxel 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 tissue voxel dissected by LCM into the PCR tube cap and MS-compatible surfactant-assisted one-pot voxel processing in the collection cap. This convenient method allows reproducible label-free quantification of ∼900 and ∼4,600 proteins for single voxel from fresh frozen human spleen tissue at 20 µm × 20 µm × 10 µm (close to single cells) and 200 µm × 200 µm × 10 µm (∼100 cells), respectively. 100s-1000s of protein signatures with differential expression levels were identified to be spatially resolved between spleen red and white pulp regions depending on the voxel size. Region-specific signaling pathways were enriched from single voxel proteomics data. Antibody-based CODEX imaging was used to validate label-free MS quantitation for single voxel analysis. The wcSOP-MS method paves the way for routine robust single voxel proteomics and spatial proteomics.

Proteome Mapping of the Human Pancreatic Islet Microenvironment Reveals Endocrine-Exocrine Signaling Sphere of Influence.

The need for a clinically accessible method with the ability to match protein activity within heterogeneous tissues is currently unmet by existing technologies. Our proteomics sample preparation platform, named microPOTS (Microdroplet Processing in One pot for Trace Samples), can be used to measure relative protein abundance in micron-scale samples alongside the spatial location of each measurement, thereby tying biologically interesting proteins and pathways to distinct regions. However, given the smaller pixel/voxel number and amount of tissue measured, standard mass spectrometric analysis pipelines have proven inadequate. Here we describe how existing computational approaches can be adapted to focus on the specific biological questions asked in spatial proteomics experiments. We apply this approach to present an unbiased characterization of the human islet microenvironment comprising the entire complex array of cell types involved while maintaining spatial information and the degree of the islet's sphere of influence. We identify specific functional activity unique to the pancreatic islet cells and demonstrate how far their signature can be detected in the adjacent tissue. Our results show that we can distinguish pancreatic islet cells from the neighboring exocrine tissue environment, recapitulate known biological functions of islet cells, and identify a spatial gradient in the expression of RNA processing proteins within the islet microenvironment.

Coupling microdroplet-based sample preparation, multiplexed isobaric labeling, and nanoflow peptide fractionation for deep proteome profiling of tissue microenvironment.

There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity at a cell-type-specific level to better understand and predict the function of complex biological systems, such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverages due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (Microdroplet Processing in One pot for Trace Samples), the multiplexed isobaric labelling, and a nanoflow peptide fractionation approach. The integrated workflow allowed to maximize proteome coverage of laser-isolated tissue samples containing nanogram proteins. We demonstrated the deep spatial proteomics can quantify more than 5,000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 µm2) and reveal unique islet microenvironments.

Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform.

Conventional proteomic approaches measure the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of signals arising from subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot unambiguously define and quantify proteoforms, which are intact (i.e., functional) forms of proteins capturing genetic variations, alternatively spliced transcripts and posttranslational modifications. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantitation directly from tissue sections. The spatial TDP platform consisted of a nanodroplet processing in one pot for trace samples-based sample preparation system and an laser capture microdissection-based cell isolation system. We improved the nanodroplet processing in one pot for trace samples sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ∼200 cultured cells as test samples, this approach increased total proteoform identifications from 493 to 700; with newly identified proteoforms primarily corresponding to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed laser capture microdissection-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 509 proteoforms within the union of top-down mass spectrometry-based proteoform identification and characterization and TDPortal identifications to match with features from protein mass extractor. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential posttranslational modification-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.

A streamlined tandem tip-based workflow for sensitive nanoscale phosphoproteomics.

Effective phosphoproteome of nanoscale sample analysis remains a daunting task, primarily due to significant sample loss associated with non-specific surface adsorption during enrichment of low stoichiometric phosphopeptide. We develop a tandem tip phosphoproteomics sample preparation method that is capable of sample cleanup and enrichment without additional sample transfer, and its integration with our recently developed SOP (Surfactant-assisted One-Pot sample preparation) and iBASIL (improved Boosting to Amplify Signal with Isobaric Labeling) approaches provides a streamlined workflow enabling sensitive, high-throughput nanoscale phosphoproteome measurements. This approach significantly reduces both sample loss and processing time, allowing the identification of >3000 (>9500) phosphopeptides from 1 (10) µg of cell lysate using the label-free method without a spectral library. It also enables precise quantification of ~600 phosphopeptides from 100 sorted cells (single-cell level input for the enriched phosphopeptides) and ~700 phosphopeptides from human spleen tissue voxels with a spatial resolution of 200 µm (equivalent to ~100 cells) in a high-throughput manner. The new workflow opens avenues for phosphoproteome profiling of mass-limited samples at the low nanogram level.

An optimized approach and inflation media for obtaining complimentary mass spectrometry-based omics data from human lung tissue.

Human disease states are biomolecularly multifaceted and can span across phenotypic states, therefore it is important to understand diseases on all levels, across cell types, and within and across microanatomical tissue compartments. To obtain an accurate and representative view of the molecular landscape within human lungs, this fragile tissue must be inflated and embedded to maintain spatial fidelity of the location of molecules and minimize molecular degradation for molecular imaging experiments. Here, we evaluated agarose inflation and carboxymethyl cellulose embedding media and determined effective tissue preparation protocols for performing bulk and spatial mass spectrometry-based omics measurements. Mass spectrometry imaging methods were optimized to boost the number of annotatable molecules in agarose inflated lung samples. This optimized protocol permitted the observation of unique lipid distributions within several airway regions in the lung tissue block. Laser capture microdissection of these airway regions followed by high-resolution proteomic analysis allowed us to begin linking the lipidome with the proteome in a spatially resolved manner, where we observed proteins with high abundance specifically localized to the airway regions. We also compared our mass spectrometry results to lung tissue samples preserved using two other inflation/embedding media, but we identified several pitfalls with the sample preparation steps using this preservation method. Overall, we demonstrated the versatility of the inflation method, and we can start to reveal how the metabolome, lipidome, and proteome are connected spatially in human lungs and across disease states through a variety of different experiments.

Spatial Mapping of Plant N-Glycosylation Cellular Heterogeneity Inside Soybean Root Nodules Provided Insights Into Legume-Rhizobia Symbiosis.

Although ubiquitously present, information on the function of complex N-glycan posttranslational modification in plants is very limited and is often neglected. In this work, we adopted an enzyme-assisted matrix-assisted laser desorption/ionization mass spectrometry imaging strategy to visualize the distribution and identity of N-glycans in soybean root nodules at a cellular resolution. We additionally performed proteomics analysis to probe the potential correlation to proteome changes during symbiotic rhizobia-legume interactions. Our ion images reveal that intense N-glycosylation occurs in the sclerenchyma layer, and inside the infected cells within the infection zone, while morphological structures such as the cortex, uninfected cells, and cells that form the attachment with the root are fewer N-glycosylated. Notably, we observed different N-glycan profiles between soybean root nodules infected with wild-type rhizobia and those infected with mutant rhizobia incapable of efficiently fixing atmospheric nitrogen. The majority of complex N-glycan structures, particularly those with characteristic Lewis-a epitopes, are more abundant in the mutant nodules. Our proteomic results revealed that these glycans likely originated from proteins that maintain the redox balance crucial for proper nitrogen fixation, but also from enzymes involved in N-glycan and phenylpropanoid biosynthesis. These findings indicate the possible involvement of Lewis-a glycans in these critical pathways during legume-rhizobia symbiosis.

Diversity of killer cell immunoglobulin-like receptor genes in Pacific Islands populations.

Killer immunoglobulin-like receptors (KIRs) regulate the activity of NK and T cells through interaction with specific HLA class I molecules on target cells. To date, 16 KIR genes and pseudogenes have been identified. Diversity in KIR gene content and KIR allelic and haplotype polymorphism has been observed between different ethnic groups. Here, we present data on the KIR gene distribution in Pacific Islands populations. Sixteen KIR genes were observed in Pacific Islands populations from the Cook Islands, Samoa, Tokelau, and Tonga. The majority of KIR genes were present at similar frequencies between the four populations with KIR2DL4, KIR3DL2, and KIR3DP1 genes observed in all individuals. Commonly observed KIR genes in Pacific Islands populations (pooled frequencies) were KIR2DL1 (0.77), KIR2DL3 (0.77), KIR3DL1 (0.65), KIR3DL3 (0.93), KIR2DS4/1D (0.78), and KIR2DP1 (0.82), compared to the less-frequently observed KIR2DL2 (0.27), KIR2DL5 (0.30), KIR2DS1 (0.19), KIR2DS2 (0.27), KIR2DS3 (0.16), KIR2DS5 (0.17), and KIR3DS1 (0.18) genes. Differences in KIR gene frequency distributions were observed between the Pacific Islands populations and when compared to other populations. Sixty-nine different genotypes were identified, with five genotypes accounting for more then 50% of all genotypes observed. The number of genotypes observed in each population was similar in the Cook Islands, Samoan, and Tokelauan populations (19, 18, and 19, respectively), but 26 different genotypes were observed in Tongans. The putative haplotype A was predominantly observed over haplotype B in all Pacific Islands populations. Significant linkage disequilibrium was observed for a number of KIR gene pairs.

Routine testing for mismatch repair deficiency in sporadic colorectal cancer is justified.

This study prospectively examines the accuracy of immunohistochemical staining in the identification of mismatch repair defective (MMRD) colorectal cancer in routine clinical practice. The potential impact of this information on decisions regarding adjuvant treatment and germline testing were quantified. A consecutive series of fresh tissue (836 cancers) was obtained from 786 individuals undergoing curative surgery for colorectal cancer at one institution. As part of normal practice, each tumour was screened for the expression of MLH1 and MSH2 by immunohistochemical staining (IHC) and relevant clinicopathological details were documented. Microsatellite instability (MSI) was assessed using standard markers. Overall, 108 (13%) tumours showed loss of staining for either MLH1 (92 tumours) or MSH2 (16 tumours). The positive predictive value of mismatch repair IHC when used alone in the detection of MSI tumours was 88%, and the negative predictive value was 97%. Specificity and positive predictive value were improved by correlation with microsatellite status. Tumour stage (HR 3.5, 95% CI 2.0-6.0), vascular space invasion (HR 1.9, 95% CI 1.2-3.0) and mismatch repair deficiency (HR 0.2, 95% CI 0.05-0.87) were independent prognostic factors in stages II and III disease. Screening by mismatch repair IHC could reasonably have been expected to prevent ineffective treatment in 3.6% of stage II and 7.6% of stage III patients. The frequency of germline mismatch repair mutations was 0.8%, representing six unsuspected hereditary non-polyposis colorectal cancer (HNPCC) cases. Routine screening of colorectal cancers by mismatch repair IHC identifies individuals at low risk of relapse, and can prevent unnecessary adjuvant treatments in a significant number of individuals. Abnormal immunohistochemistry should be confirmed by microsatellite testing to ensure that false-positive results do not adversely impact on treatment decisions.

Identification of the bruton tyrosine kinase (BTK) gene mutations in 20 Australian families with X-linked agammaglobulinemia (XLA).

X-linked agammaglobulinemia (XLA) is an immunodeficiency caused by mutations in the Bruton tyrosine kinase (BTK) gene. Twenty Australian patients with an XLA phenotype, from 15 unrelated families, were found to have 14 mutations. Five of the mutations were previously described c.83G>A (p.R28H), c.862C>T (p.R288W), c.904G>A (p.R302G), c.1535T>C (p.L512P), c.700C>T (p.Q234X), while nine novel mutations were identified: four missense c.82C>A (p.R28S), c.494G>A (p.C165Y), c.464G>A (p.C155Y), c.1750G>A (p.G584E), one deletion c.142_144delAGAAGA (p.R48_G50del), and four splice site mutations c.241-2A>G, c.839+4A>G, c.1350-2A>G, c.1566+1G>A. Carrier analysis was performed in 10 mothers and 11 female relatives. The results of this study further support the notion that molecular genetic testing represents an important tool for definitive and early diagnosis of XLA and may allow accurate carrier status and prenatal diagnosis.

Intragenic PTEN/MMAC1 loss of heterozygosity in conventional (clear-cell) renal cell carcinoma is associated with poor patient prognosis.

Inactivation of the PTEN/MMAC1 tumor suppressor gene has been linked to tumor progression in several human malignancies. However, the role of PTEN/MMAC1 in the development and progression of the major renal cell carcinoma morphotypes remains controversial. We examined microdissected specimens from 80 conventional (clear cell) renal cell carcinomas (cRCC), 27 papillary renal cell carcinomas (pRCC), and 16 chromophobe renal cell carcinomas (chRCC) for loss of heterozygosity (LOH) at and around the PTEN/MMAC1 locus and for mutations in the PTEN/MMAC1 gene. The results of the molecular studies were correlated with tumor stage, grade, and patient survival. LOH at one or more of the examined loci occurred in 37.5% of cRCC, 29.6% of pRCC and 87.5% of chRCC specimens. The chRCC specimens showed increasing rates of LOH the further that a marker was located toward the q telomer of chromosome 10, consistent with nonspecific genetic disarray in genomically highly unstable tumors. No such pattern was discernible in the cRCC and pRCC. In the cRCC, LOH at intragenic PTEN/MMAC1 microsatellite markers (indicating deletional events involving the actual PTEN/MMAC1 gene) was significantly associated with tumor death, with 85.7% of such patients dying, whereas only 45.3% of patients without intragenic LOH died (P =.018). There were no PTEN/MMAC1 mutations in our specimens. We conclude that PTEN/MMAC1 inactivation may play a role in the progression of cRCC. Biallelic inactivation may preferentially occur by nonmutational mechanisms, or, alternatively, haploinsufficiency of PTEN/MMAC1 may be sufficient to affect tumor progression in cRCC.