IntLIM 2.0: identifying multi-omic relationships dependent on discrete or continuous phenotypic measurements.

Motivation: IntLIM uncovers phenotype-dependent linear associations between two types of analytes (e.g. genes and metabolites) in a multi-omic dataset, which may reflect chemically or biologically relevant relationships. Results: The new IntLIM R package includes newly added support for generalized data types, covariate correction, continuous phenotypic measurements, model validation and unit testing. IntLIM analysis uncovered biologically relevant gene-metabolite associations in two separate datasets, and the run time is improved over baseline R functions by multiple orders of magnitude. Availability and implementation: IntLIM is available as an R package with a detailed vignette (https://github.com/ncats/IntLIM) and as an R Shiny app (see Supplementary Figs S1-S6) (https://intlim.ncats.io/). Supplementary information: Supplementary data are available at Bioinformatics Advances online.

RaMP-DB 2.0: a renovated knowledgebase for deriving biological and chemical insight from metabolites, proteins, and genes.

MOTIVATION: Functional interpretation of high-throughput metabolomic and transcriptomic results is a crucial step in generating insight from experimental data. However, pathway and functional information for genes and metabolites are distributed among many siloed resources, limiting the scope of analyses that rely on a single knowledge source. RESULTS: RaMP-DB 2.0 is a web interface, relational database, API and R package designed for straightforward and comprehensive functional interpretation of metabolomic and multi-omic data. RaMP-DB 2.0 has been upgraded with an expanded breadth and depth of functional and chemical annotations (ClassyFire, LIPID MAPS, SMILES, InChIs, etc.), with new data types related to metabolites and lipids incorporated. To streamline entity resolution across multiple source databases, we have implemented a new semi-automated process, thereby lessening the burden of harmonization and supporting more frequent updates. The associated RaMP-DB 2.0 R package now supports queries on pathways, common reactions (e.g. metabolite-enzyme relationship), chemical functional ontologies, chemical classes and chemical structures, as well as enrichment analyses on pathways (multi-omic) and chemical classes. Lastly, the RaMP-DB web interface has been completely redesigned using the Angular framework. AVAILABILITY AND IMPLEMENTATION: The code used to build all components of RaMP-DB 2.0 are freely available on GitHub at https://github.com/ncats/ramp-db, https://github.com/ncats/RaMP-Client/ and https://github.com/ncats/RaMP-Backend. The RaMP-DB web application can be accessed at https://rampdb.nih.gov/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Dietary Energy Intake and Presence of Aberrant Crypt Foci Are Associated with Phospholipid, Purine, and Taurine Metabolite Abundances in C57BL/6N Mouse Colon.

SCOPE: Colon metabolomes associated with high-fat (H) versus energy-restricted (E) diets in early colorectal cancer (CRC) models have never been directly compared. The objectives of this study are to elucidate metabolites associated with diet, aberrant crypt foci (ACF), and diet:ACF interaction, using a lifetime murine model. METHODS AND RESULTS: Three-week-old mice consumed control (C), E, or H initiation diets for 18 weeks. ACF formation is initiated weeks 16-21 with azoxymethane injections, followed by progression diet crossover (to C, E, or H) through week 60. Colon extracts are analyzed using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). Metabolites associated with diet, ACF, or diet:ACF are determined using regression models (FDR-adjusted p-value <0.05). No metabolites are significantly associated with initiation diets, but concentrations of acylcarnitines and phospholipids are associated with C, E, and H progression diets. Purines, taurine, and phospholipids are associated with ACF presence. No significant associations between metabolites and diet:ACF interaction are observed. CONCLUSIONS: These results suggest that recent, rather than early-life, diet is more closely associated with the colon metabolome, particularly lipid metabolism. Results from this study also provide candidate biomarkers of early CRC development and provide support for the importance of early diet on influencing pre-CRC risk.

Stressor-Induced Reduction in Cognitive Behavior is Associated with Impaired Colonic Mucus Layer Integrity and is Dependent Upon the LPS-Binding Protein Receptor CD14.

Purpose: Commensal microbes are impacted by stressor exposure and are known contributors to cognitive and social behaviors, but the pathways through which gut microbes influence stressor-induced behavioral changes are mostly unknown. A murine social stressor was used to determine whether host-microbe interactions are necessary for stressor-induced inflammation, including neuroinflammation, that leads to reduced cognitive and social behavior. Methods: C57BL/6 male mice were exposed to a paired fighting social stressor over a 1 hr period for 6 consecutive days. Y-maze and social interaction behaviors were tested following the last day of the stressor. Serum cytokines and lipopolysaccharide binding protein (LBP) were measured and the number and morphology of hippocampal microglia determined via immunohistochemistry. Intestinal mucous thickness and antimicrobial peptide expression were determined via fluorescent staining and real-time PCR (respectively) and microbial community composition was assessed using 16S rRNA gene amplicon sequencing. To determine whether the microbiota or the LBP receptor (CD14) are necessary for stressor-induced behavioral changes, experiments were performed in mice treated with a broad-spectrum antibiotic cocktail or in CD14-/- mice. Results: The stressor reduced Y-maze spontaneous alternations, which was accompanied by increased microglia in the hippocampus, increased circulating cytokines (eg, IL-6, TNF-α) and LBP, and reduced intestinal mucus thickness while increasing antimicrobial peptides and cytokines. These stressor-induced changes were largely prevented in mice given broad-spectrum antibiotics and in CD14-/- mice. In contrast, social stressor-induced alterations of social behavior were not microbe-dependent. Conclusion: Stressor-induced cognitive deficits involve enhanced bacterial interaction with the intestine, leading to low-grade, CD14-dependent, inflammation.

Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources.

As researchers are increasingly able to collect data on a large scale from multiple clinical and omics modalities, multi-omics integration is becoming a critical component of metabolomics research. This introduces a need for increased understanding by the metabolomics researcher of computational and statistical analysis methods relevant to multi-omics studies. In this review, we discuss common types of analyses performed in multi-omics studies and the computational and statistical methods that can be used for each type of analysis. We pinpoint the caveats and considerations for analysis methods, including required parameters, sample size and data distribution requirements, sources of a priori knowledge, and techniques for the evaluation of model accuracy. Finally, for the types of analyses discussed, we provide examples of the applications of corresponding methods to clinical and basic research. We intend that our review may be used as a guide for metabolomics researchers to choose effective techniques for multi-omics analyses relevant to their field of study.

StormSense: A New Integrated Network of IoT Water Level Sensors in the Smart Cities of Hampton Roads, VA.

Propagation of cost-effective water level sensors powered through the Internet of Things (IoT) has expanded the available offerings of ingestible data streams at the disposal of modern smart cities. StormSense is an IoT-enabled inundation forecasting research initiative and an active participant in the Global City Teams Challenge seeking to enhance flood preparedness in the smart cities of Hampton Roads, VA for flooding resulting from storm surge, rain, and tides. In this study, we present the results of the new StormSense water level sensors to help establish the "regional resilience monitoring network" noted as a key recommendation from the Intergovernmental Pilot Project. To accomplish this, the Commonwealth Center for Recurrent Flooding Resiliency's Tidewatch tidal forecast system is being used as a starting point to integrate the extant (NOAA) and new (USGS and StormSense) water level sensors throughout the region, and demonstrate replicability of the solution across the cities of Newport News, Norfolk, and Virginia Beach within Hampton Roads, VA. StormSense's network employs a mix of ultrasonic and radar remote sensing technologies to record water levels during 2017 Hurricanes Jose and Maria. These data were used to validate the inundation predictions of a street-level hydrodynamic model (5-m resolution), while the water levels from the sensors and the model were concomitantly validated by a temporary water level sensor deployed by the USGS in the Hague, and crowd-sourced GPS maximum flooding extent observations from the Sea Level Rise app, developed in Norfolk, VA.

HIV testing histories and risk factors among migrants and recent immigrants who received rapid HIV testing from three community-based organizations.

Migrants and recent immigrants in the US constitute a large population that is vulnerable to HIV. From March 2005 to February 2007, three community-based organizations conducted rapid HIV testing among migrants in five states. Participants were asked to complete a survey on sociodemographics, HIV-risk behaviors, and HIV-testing histories with the aim of understanding factors associated with HIV testing. Among 5,247 persons tested, 6 (0.1 %) were HIV-positive. Among 3,135 persons who completed surveys, more than half had never been tested for HIV previously (59 %). Participants reported high levels of HIV-risk behaviors in the past year, including 2 or more sex partners (45 %), sex while high/drunk (30 %), and transactional sex (29 %). Multivariate analysis identified several factors independently associated with decreased likelihood of prior HIV testing, including poor spoken English. Continued efforts are needed to ensure that migrant populations have improved access to HIV testing and prevention services. Understanding factors associated with migrants' lack of previous HIV testing may help focus these efforts.

A new class of peroxisome proliferator-activated receptor gamma (PPARgamma) agonists that inhibit growth of breast cancer cells: 1,1-Bis(3'-indolyl)-1-(p-substituted phenyl)methanes.

1,1-Bis(3'-indolyl)-1-(p-trifluoromethylphenyl)methane (DIM-C-pPhCF(3)) and several p-substituted phenyl analogues have been investigated as a new class of peroxisome proliferator-activated receptor gamma (PPARgamma) agonists. Structure-activity studies in PPARgamma-dependent transactivation assays in MCF-7 breast cancer cells show that 5-20 micro M concentrations of compounds containing p-trifluoromethyl, t-butyl, cyano, dimethylamino, and phenyl groups were active, whereas p-methyl, hydrogen, methoxy, hydroxyl, or halogen groups were inactive as PPARgamma agonists. Induction of PPARgamma-dependent transactivation by 15-deoxy-Delta12,14-prostaglandin J2 (PGJ2) and DIM-C-pPhCF(3) was inhibited in MCF-7 cells cotreated with the PPARgamma-specific antagonist N-(4'-aminopyridyl)-2-chloro-5-nitrobenzamide. In mammalian two-hybrid assays, DIM-C-pPhCF(3) and PGJ2 (5-20 micro M) induced interactions of PPARgamma with steroid receptor coactivator (SRC) 1, SRC2 (TIFII), and thyroid hormone receptor-associated protein 220 but not with SRC3 (AIB1). In contrast, DIM-C-pPhCF(3), but not PGJ2, induced interactions of PPARgamma with PPARgamma coactivator-1. C-substituted diindolylmethanes inhibit carcinogen-induced rat mammary tumor growth, induce differentiation in 3T3-L1 preadipocytes, inhibit MCF-7 cell growth and G(0)/G(1)-S phase progression, induce apoptosis, and down-regulate cyclin D1 protein and estrogen receptor alpha in breast cancer cells. These compounds are a novel class of synthetic PPARgamma agonists that induce responses in MCF-7 cells similar to those observed for PGJ2.