Plasma proteome of growing tumors.

Early detection of cancer is vital for the best chance of successful treatment, but half of all cancers are diagnosed at an advanced stage. A simple and reliable blood screening test applied routinely would therefore address a major unmet medical need. To gain insight into the value of protein biomarkers in early detection and stratification of cancer we determined the time course of changes in the plasma proteome of mice carrying transplanted human lung, breast, colon, or ovarian tumors. For protein measurements we used an aptamer-based assay which simultaneously measures ~ 5000 proteins. Along with tumor lineage-specific biomarkers, we also found 15 markers shared among all cancer types that included the energy metabolism enzymes glyceraldehyde-3-phosphate dehydrogenase, glucose-6-phophate isomerase and dihydrolipoyl dehydrogenase as well as several important biomarkers for maintaining protein, lipid, nucleotide, or carbohydrate balance such as tryptophanyl t-RNA synthetase and nucleoside diphosphate kinase. Using significantly altered proteins in the tumor bearing mice, we developed models to stratify tumor types and to estimate the minimum detectable tumor volume. Finally, we identified significantly enriched common and unique biological pathways among the eight tumor cell lines tested.

Tick Microbiomes in Neotropical Forest Fragments Are Best Explained by Tick-Associated and Environmental Factors Rather than Host Blood Source.

The composition of tick microbiomes varies both within and among tick species. Whether this variation is intrinsic (related to tick characteristics) or extrinsic (related to vertebrate host and habitat) is poorly understood but important, as microbiota can influence the reproductive success and vector competence of ticks. We aimed to uncover what intrinsic and extrinsic factors best explain the microbial composition and taxon richness of 11 species of neotropical ticks collected from eight species of small mammals in 18 forest fragments across central Panama. Microbial richness varied among tick species, life stages, and collection sites but was not related to host blood source. Microbiome composition was best explained by tick life stage, with bacterial assemblages of larvae being a subset of those of nymphs. Collection site explained most of the bacterial taxa with differential abundance across intrinsic and extrinsic factors. Francisella and Rickettsia were highly prevalent, but their proportional abundance differed greatly among tick species, and we found both positive and negative cooccurrence between members of these two genera. Other tick endosymbionts (e.g., Coxiella and Rickettsiella) were associated with specific tick species. In addition, we detected Anaplasma and Bartonella in several tick species. Our results indicate that the microbial composition and richness of neotropical ticks are principally related to intrinsic factors (tick species and life stage) and collection site. Taken together, our analysis informs how tick microbiomes are structured and can help anchor our understanding of tick microbiomes from tropical environments more broadly.IMPORTANCE Blood-feeding arthropod microbiomes often play important roles in disease transmission, yet the factors that structure tick microbial communities in the Neotropics are unknown. Utilizing ticks collected from live animals in neotropical forest fragments, this study teases apart the contributions of intrinsic and extrinsic tick-associated factors on tick microbial composition as well as which specific microbes contribute to differences across tick species, tick life stages, the mammals they fed on, and the locations from where they were sampled. Furthermore, this study provides revelations of how notable tick-associated bacterial genera are interacting with other tick-associated microbes as well as the forest animals they encounter.

Impact of Kidney Function on the Blood Proteome and on Protein Cardiovascular Risk Biomarkers in Patients With Stable Coronary Heart Disease.

Background Chronic kidney disease (CKD) confers increased cardiovascular risk, not fully explained by traditional factors. Proteins regulate biological processes and inform the risk of diseases. Thus, in 938 patients with stable coronary heart disease from the Heart and Soul cohort, we quantified 1054 plasma proteins using modified aptamers (SOMAscan) to: (1) discern how reduced glomerular filtration influences the circulating proteome, (2) learn of the importance of kidney function to the prognostic information contained in recently identified protein cardiovascular risk biomarkers, and (3) identify novel and even unique cardiovascular risk biomarkers among individuals with CKD. Methods and Results Plasma protein levels were correlated to estimated glomerular filtration rate (eGFR) using Spearman-rank correlation coefficients. Cox proportional hazard models were used to estimate the association between individual protein levels and the risk of the cardiovascular outcome (first among myocardial infarction, stroke, heart failure hospitalization, or mortality). Seven hundred and nine (67.3%) plasma proteins correlated with eGFR at P<0.05 (ρ 0.06-0.74); 218 (20.7%) proteins correlated with eGFR moderately or strongly (ρ 0.2-0.74). Among the previously identified 196 protein cardiovascular biomarkers, just 87 remained prognostic after correction for eGFR. Among patients with CKD (eGFR <60 mL/min per 1.73 m2), we identified 21 protein cardiovascular risk biomarkers of which 8 are unique to CKD. Conclusions CKD broadly alters the composition of the circulating proteome. We describe protein biomarkers capable of predicting cardiovascular risk independently of glomerular filtration, and those that are prognostic of cardiovascular risk specifically in patients with CKD and even unique to patients with CKD.

Proteomic Profiles in Advanced Age-Related Macular Degeneration Using an Aptamer-Based Proteomic Technology.

PURPOSE: To explore top-ranked plasma proteins related to neovascular age-related macular degeneration (AMD) and geographic atrophy (GA), and explore pathways related to neovascular AMD and GA. METHODS: We conducted a pilot study of patients with neovascular AMD (n = 10), GA (n = 10), and age-matched cataract controls (n = 10) who were recruited into an AMD registry. We measured 4001 proteins in ethylenediaminetetraacetic acid plasma samples using an aptamer-based proteomic technology. Relative concentrations of each of 4001 proteins were log (base 2) transformed and compared between cases of neovascular AMD and GA versus controls using linear regression. Pathway analysis was conducted using pathways downloaded from Reactome. RESULTS: In this pilot study, higher levels of vinculin and lower levels of CD177 were found in patients with neovascular AMD compared with controls. Neuregulin-4 was higher and soluble intercellular adhesion molecule-1 was lower in patients with GA compared with controls. For neovascular AMD, cargo trafficking to the periciliary membrane, fibroblast growth factor receptor 3b ligand binding and activation, and vascular endothelial growth factor-related pathways were in the top ranked pathways. The top-ranked pathways for GA included several related to ErbB4 signaling. CONCLUSIONS: We found different proteins and different pathways associated with neovascular AMD and GA. Vinculin and some of the top-ranked pathways have been previously associated with AMD, whereas others have not been described. TRANSLATIONAL RELEVANCE: Biomarkers identified in plasma likely reflect systemic alterations in protein expression and may improve our understanding of the mechanisms leading to AMD.

Improving Assessment of Drug Safety Through Proteomics: Early Detection and Mechanistic Characterization of the Unforeseen Harmful Effects of Torcetrapib.

BACKGROUND: Early detection of adverse effects of novel therapies and understanding of their mechanisms could improve the safety and efficiency of drug development. We have retrospectively applied large-scale proteomics to blood samples from ILLUMINATE (Investigation of Lipid Level Management to Understand its Impact in Atherosclerotic Events), a trial of torcetrapib (a cholesterol ester transfer protein inhibitor), that involved 15 067 participants at high cardiovascular risk. ILLUMINATE was terminated at a median of 550 days because of significant absolute increases of 1.2% in cardiovascular events and 0.4% in mortality with torcetrapib. The aims of our analysis were to determine whether a proteomic analysis might reveal biological mechanisms responsible for these harmful effects and whether harmful effects of torcetrapib could have been detected early in the ILLUMINATE trial with proteomics. METHODS: A nested case-control analysis of paired plasma samples at baseline and at 3 months was performed in 249 participants assigned to torcetrapib plus atorvastatin and 223 participants assigned to atorvastatin only. Within each treatment arm, cases with events were matched to controls 1:1. Main outcomes were a survey of 1129 proteins for discovery of biological pathways altered by torcetrapib and a 9-protein risk score validated to predict myocardial infarction, stroke, heart failure, or death. RESULTS: Plasma concentrations of 200 proteins changed significantly with torcetrapib. Their pathway analysis revealed unexpected and widespread changes in immune and inflammatory functions, as well as changes in endocrine systems, including in aldosterone function and glycemic control. At baseline, 9-protein risk scores were similar in the 2 treatment arms and higher in participants with subsequent events. At 3 months, the absolute 9-protein derived risk increased in the torcetrapib plus atorvastatin arm compared with the atorvastatin-only arm by 1.08% (P=0.0004). Thirty-seven proteins changed in the direction of increased risk of 49 proteins previously associated with cardiovascular and mortality risk. CONCLUSIONS: Heretofore unknown effects of torcetrapib were revealed in immune and inflammatory functions. A protein-based risk score predicted harm from torcetrapib within just 3 months. A protein-based risk assessment embedded within a large proteomic survey may prove to be useful in the evaluation of therapies to prevent harm to patients. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00134264.

Parallel Mapping of Antibiotic Resistance Alleles in Escherichia coli.

Chemical genomics expands our understanding of microbial tolerance to inhibitory chemicals, but its scope is often limited by the throughput of genome-scale library construction and genotype-phenotype mapping. Here we report a method for rapid, parallel, and deep characterization of the response to antibiotics in Escherichia coli using a barcoded genome-scale library, next-generation sequencing, and streamlined bioinformatics software. The method provides quantitative growth data (over 200,000 measurements) and identifies contributing antimicrobial resistance and susceptibility alleles. Using multivariate analysis, we also find that subtle differences in the population responses resonate across multiple levels of functional hierarchy. Finally, we use machine learning to identify a unique allelic and proteomic fingerprint for each antibiotic. The method can be broadly applied to tolerance for any chemical from toxic metabolites to next-generation biofuels and antibiotics.

Genome-Wide Tuning of Protein Expression Levels to Rapidly Engineer Microbial Traits.

The reliable engineering of biological systems requires quantitative mapping of predictable and context-independent expression over a broad range of protein expression levels. However, current techniques for modifying expression levels are cumbersome and are not amenable to high-throughput approaches. Here we present major improvements to current techniques through the design and construction of E. coli genome-wide libraries using synthetic DNA cassettes that can tune expression over a ∼10(4) range. The cassettes also contain molecular barcodes that are optimized for next-generation sequencing, enabling rapid and quantitative tracking of alleles that have the highest fitness advantage. We show these libraries can be used to determine which genes and expression levels confer greater fitness to E. coli under different growth conditions.

Toward effective probiotics for autism and other neurodevelopmental disorders.

Hsaio and colleagues link gut microbes to autism spectrum disorders (ASD) in a mouse model. They show that ASD symptoms are triggered by compositional and structural shifts of microbes and associated metabolites, but symptoms are relieved by a Bacteroides fragilis probiotic. Thus probiotics may provide therapeutic strategies for neurodevelopmental disorders.

Genome-scale identification and characterization of ethanol tolerance genes in Escherichia coli.

The identification of relevant gene targets for engineering a desired trait is a key step in combinatorial strain engineering. Here, we applied the multi-Scalar Analysis of Library Enrichments (SCALEs) approach to map ethanol tolerance onto 1,000,000 genomic-library clones in Escherichia coli. We assigned fitness scores to each of the ∼4,300 genes in E. coli, and through follow-up confirmatory studies identified 9 novel genetic targets (12 genes total) that increase E. coli ethanol tolerance (up to 6-fold improved growth). These genetic targets are involved in the processes related to cell membrane composition, translation, serine biosynthesis, and transcription regulation. Transcriptional profiling of the ethanol stress response in 5 of these ethanol-tolerant clones revealed a total of 700 genes with significantly altered expression (mapped to 615 significantly enriched gene ontology terms) across all five clones, with similar overall changes in global gene expression between two clone clusters. All ethanol-tolerant clones analyzed shared 6% of the overexpressed genes and showed enrichment for transcription regulation-related GO terms. iTRAQ-based proteomic analysis of ethanol-tolerant strains identified upregulation of proteins related to ROS mitigation, fatty acid biosynthesis, and vitamin biosynthesis as compared to the parent strain's ethanol response. The approach we outline here will be useful for engineering a variety of other traits and further improvements in alcohol tolerance.