Faculty Bibliography

OBJECTIVE:To characterize the ecological effects of biologic therapies on the gut bacterial and fungal microbiome of psoriatic arthritis (PsA)/spondyloarthritis (SpA) patients. METHODS:Fecal samples from PsA/SpA patients pre- and post-treatment with tumor necrosis factor inhibitors (TNFi; n=15) or an anti-interleukin (IL)-17A monoclonal antibody inhibitor (IL-17i; n=14) underwent sequencing (16S, ITS and shotgun metagenomics) and computational microbiome analysis. Fecal levels of fatty acid metabolites and cytokines/proteins implicated in PsA/SpA pathogenesis or intestinal inflammation were correlated with sequence data. Additionally, ileal biopsies obtained from SpA patients who developed clinically overt Crohn's disease (CD) after treatment with IL-17i (n=5) were analyzed for expression of IL-23/Th-17 related cytokines, IL-25/IL-17E-producing cells and type-2 innate lymphoid cells (ILC2s). RESULTS:There were significant shifts in abundance of specific taxa after treatment with IL-17i compared to TNFi, particularly Clostridiales (p=0.016) and Candida albicans (p=0.041). These subclinical alterations correlated with changes in bacterial community co-occurrence, metabolic pathways, IL-23/Th17-related cytokines and various fatty acids. Ileal biopsies showed that clinically overt CD was associated with expansion of IL-25/IL-17E-producing tuft cells and ILC2s (p<0.05) compared to pre-IL-17i treatment levels. CONCLUSION/CONCLUSIONS:In a subgroup of SpA patients, the initiation of IL-17A blockade correlated with features of subclinical gut inflammation and intestinal dysbiosis of certain bacterial and fungal taxa, most notably C. albicans. Further, IL-17i-related CD was associated with overexpression of IL-25/IL-17E-producing tuft cells and ILC2s. These results may help to explain the potential link between inhibition of a specific IL-17 pathway and the (sub)clinical gut inflammation observed in SpA.

Background and aims: Chronic granulomatous disease (CGD) is characterized by recurrent infections and inflammatory dysregulation, especially in the gut. Almost 50% of patients with CGD have CGD-associated inflammatory bowel disease (CGD-IBD), yet its pathophysiology remains poorly understood. We characterized the intestinal microbiome and metabolome in patients with CGD to determine if intestinal microbiome and metabolomic signatures could distinguish subpopulations of patients with CGD while using the metabolome to add a functional dimension to observed microbiome signatures.
Method(s): Clinical metadata and fecal samples were collected crosssectionally from healthy volunteers (HV; n=16) and patients with CGD (n=77). Metabolomic profiling and 16S rRNA (V4) sequencing was performed on fecal samples (total samples: 108; reads/sample: 15,254 to 191,415; median: 60,816).
Result(s): Samples from patients with CGD had distinct intestinal microbiome signatures and metabolomic profiles depending on genotype, presence of CGD-IBD and specific interventions (e.g. treatment with an elemental diet). Notably, samples from patients with active CGD-IBD (compared to samples from patients without a history of CGD-IBD) had significantly different alpha- and betadiversities, and were enriched for Enterococcus spp. (8.5 vs. 1.5%), Serratia spp. (8.6 vs. 3.9%) and Raoultella spp. (6.1 vs. 0.6%), while being depleted of Bacteroides spp. (9.3 vs. 23.6%). Metabolomic profiles from CGD patient samples pointed toward an aberrant metabolism of toxic ammonia waste by the intestinal microbiota compared to HV. Interestingly, use of an elemental diet to treat a patient with CGD-IBD induced long-term changes in the alpha- and beta-diversities of the patients intestinal microbiota, stabilized the intestinal metabolome, and allowed his microbial and metabolic profiles to resemble those of patients without CGD-IBD.
Conclusion(s): Intestinal microbiome and metabolomic signatures can distinguish subpopulations of patients CGD based on genotype, presence of intestinal inflammation and certain treatment interventions

The use of fixed fibroblasts from familial and sporadic Alzheimer's disease patients has previously indicated an upregulation of mitochondria-ER contacts (MERCs) as a hallmark of Alzheimer's disease. Despite its potential significance, the relevance of these results is limited because they were not extended to live neurons. Here we performed a dynamic in vivo analysis of MERCs in hippocampal neurons from McGill-R-Thy1-APP transgenic rats, a model of Alzheimer's disease-like amyloid pathology. Live FRET imaging of neurons from transgenic rats revealed perturbed 'lipid-MERCs' (gap width <10 nm), while 'Ca²⁺-MERCs' (10-20 nm gap width) were unchanged. In situ TEM showed no significant differences in the lipid-MERCs:total MERCs or lipid-MERCs:mitochondria ratios; however, the average length of lipid-MERCs was significantly decreased in neurons from transgenic rats as compared to controls. In accordance with FRET results, untargeted lipidomics showed significant decreases in levels of 12 lipids and bioenergetic analysis revealed respiratory dysfunction of mitochondria from transgenic rats. Thus, our results reveal changes in MERC structures coupled with impaired mitochondrial functions in Alzheimer's disease-related neurons.This article has an associated First Person interview with the first author of the paper.

Advanced, metastatic melanomas frequently grow in subcutaneous tissues and portend a poor prognosis. Though subcutaneous tissues are largely composed of adipocytes, the mechanisms by which adipocytes influence melanoma are poorly understood. Using in vitro and in vivo models, we find that adipocytes increase proliferation and invasion of adjacent melanoma cells. Additionally, adipocytes directly transfer lipids to melanoma cells, which alters tumor cell metabolism. Adipocyte-derived lipids are transferred to melanoma cells through the FATP/SLC27A family of lipid transporters expressed on the tumor cell surface. Among the six FATP/SLC27A family members, melanomas significantly overexpress FATP1/SLC27A1. Melanocyte-specific FATP1 expression cooperates with BRAFV600E in transgenic zebrafish to accelerate melanoma development, an effect that is similarly seen in mouse xenograft studies. Pharmacologic blockade of FATPs with the small molecule Lipofermata abrogates lipid transport into melanoma cells and reduces melanoma growth and invasion. These data demonstrate that stromal adipocytes can drive melanoma progression through FATP lipid transporters, and represents a new target aimed at interrupting adipocyte-melanoma cross-talk.

High throughput untargeted metabolomics usually relies on complementary liquid chromatography-mass spectrometry (LC-MS) methods to expand the coverage of diverse metabolites, but the integration of those methods is not fully characterized. We systematically investigated the performance of hydrophilic interaction liquid chromatography (HILIC)-MS and nanoflow reverse-phase liquid chromatography (nRPLC)-MS under 8 LC-MS settings, varying stationary phases (HILIC and C18), mobile phases (acidic and basic pH), and MS ionization modes (positive and negative). Whereas nRPLC-MS optimization was previously reported, we found in HILIC-MS (2.1 mm × 150 mm) that the optimal performance was achieved in a 90 min gradient with 100 μL/min flow rate by loading metabolite extracts from 2 mg of cell/tissue samples. Since peak features were highly compromised by contaminants, we used stable isotope labeled yeast to enhance formula identification for comparing different LC-MS conditions. The 8 LC-MS settings enabled the detection of a total of 1050 formulas, among which 78%, 73%, and 62% formulas were recovered by the best combination of 4, 3, and 2 LC-MS settings, respectively. Moreover, these yeast samples were harvested in the presence or absence of nitrogen starvation, enabling quantitative comparisons of altered formulas and metabolite structures, followed by validation with selected synthetic metabolites. The results revealed that nitrogen starvation downregulated amino acid components but upregulated uridine-related metabolism. In summary, this study introduces a thorough evaluation of hydrophilicity and hydrophobicity based LC-MS and provides information for selecting complementary settings to balance throughput and efficiency during metabolomics experiments.

Metabolite identification is a crucial step in mass spectrometry (MS)-based metabolomics. However, it is still challenging to assess the confidence of assigned metabolites. We report a novel method for estimating the false discovery rate (FDR) of metabolite assignment with a target-decoy strategy, in which the decoys are generated through violating the octet rule of chemistry by adding small odd numbers of hydrogen atoms. The target-decoy strategy was integrated into JUMPm, an automated metabolite identification pipeline for large-scale MS analysis and was also evaluated with two other metabolomics tools, mzMatch and MZmine 2. The reliability of FDR calculation was examined by false data sets, which were simulated by altering MS1 or MS2 spectra. Finally, we used the JUMPm pipeline coupled to the target-decoy strategy to process unlabeled and stable-isotope-labeled metabolomic data sets. The results demonstrate that the target-decoy strategy is a simple and effective method for evaluating the confidence of high-throughput metabolite identification.

Retinoic acid (RA) is a vital morphogen for early patterning and organogenesis in the developing embryo. RA is a diffusible, lipophilic molecule that signals via nuclear RA receptor heterodimeric units that regulate gene expression by interacting with RA response elements in promoters of a significant number of genes. For precise RA signaling, a robust gradient of the morphogen is required. The developing embryo contains regions that produce RA, and specific intracellular concentrations of RA are created through local degradation mediated by Cyp26 enzymes. In order to elucidate the mechanisms by which RA executes precise developmental programs, the kinetics of RA metabolism must be clearly understood. Recent advances in techniques for endogenous RA detection and quantification have paved the way for mechanistic studies to shed light on downstream gene expression regulation coordinated by RA. It is increasingly coming to light that RA signaling operates not only as precise concentrations but also employs mechanisms of degradation and feedback inhibition to self-regulate its levels. A global gradient of RA throughout the embryo is often found concurrently with several local gradients, created by juxtaposed domains of RA synthesis and degradation. The existence of such local gradients has been found especially critical for the proper development of craniofacial structures that arise from the neural crest and the cranial placode populations. In this review we summarize the current understanding of how local gradients of RA are established in the embryo and their impact on craniofacial development.

Global metabolomics relies on highly reproducible and sensitive detection of a wide range of metabolites in biological samples. Here we report the optimization of metabolome analysis by nanoflow ultraperformance liquid chromatography coupled to high-resolution orbitrap mass spectrometry. Reliable peak features were extracted from the LC-MS runs based on mandatory detection in duplicates and additional noise filtering according to blank injections. The run-to-run variation in peak area showed a median of 14%, and the false discovery rate during a mock comparison was evaluated. To maximize the number of peak features identified, we systematically characterized the effect of sample loading amount, gradient length, and MS resolution. The number of features initially rose and later reached a plateau as a function of sample amount, fitting a hyperbolic curve. Longer gradients improved unique feature detection in part by time-resolving isobaric species. Increasing the MS resolution up to 120000 also aided in the differentiation of near isobaric metabolites, but higher MS resolution reduced the data acquisition rate and conferred no benefits, as predicted from a theoretical simulation of possible metabolites. Moreover, a biphasic LC gradient allowed even distribution of peak features across the elution, yielding markedly more peak features than the linear gradient. Using this robust nUPLC-HRMS platform, we were able to consistently analyze ~6500 metabolite features in a single 60 min gradient from 2 mg of yeast, equivalent to ~50 million cells. We applied this optimized method in a case study of drug (bortezomib) resistant and drug-sensitive multiple myeloma cells. Overall, 18% of metabolite features were matched to KEGG identifiers, enabling pathway enrichment analysis. Principal component analysis and heat map data correctly clustered isogenic phenotypes, highlighting the potential for hundreds of small molecule biomarkers of cancer drug resistance.

Deposition of insoluble protein aggregates is a hallmark of neurodegenerative diseases. The universal presence of beta-amyloid and tau in Alzheimer's disease (AD) has facilitated advancement of the amyloid cascade and tau hypotheses that have dominated AD pathogenesis research and therapeutic development. However, the underlying etiology of the disease remains to be fully elucidated. Here we report a comprehensive study of the human brain-insoluble proteome in AD by mass spectrometry. We identify 4,216 proteins, among which 36 proteins accumulate in the disease, including U1-70K and other U1 small nuclear ribonucleoprotein (U1 snRNP) spliceosome components. Similar accumulations in mild cognitive impairment cases indicate that spliceosome changes occur in early stages of AD. Multiple U1 snRNP subunits form cytoplasmic tangle-like structures in AD but not in other examined neurodegenerative disorders, including Parkinson disease and frontotemporal lobar degeneration. Comparison of RNA from AD and control brains reveals dysregulated RNA processing with accumulation of unspliced RNA species in AD, including myc box-dependent-interacting protein 1, clusterin, and presenilin-1. U1-70K knockdown or antisense oligonucleotide inhibition of U1 snRNP increases the protein level of amyloid precursor protein. Thus, our results demonstrate unique U1 snRNP pathology and implicate abnormal RNA splicing in AD pathogenesis.