In Utero Exposure to Histological Chorioamnionitis Primes the Exometabolomic Profiles of Preterm CD4+ T Lymphocytes.

Histological chorioamnionitis (HCA) is an intrauterine inflammatory condition that increases the risk for preterm birth, death, and disability because of persistent systemic and localized inflammation. The immunological mechanisms sustaining this response in the preterm newborn remain unclear. We sought to determine the consequences of HCA exposure on the fetal CD4+ T lymphocyte exometabolome. We cultured naive CD4+ T lymphocytes from HCA-positive and -negative preterm infants matched for gestational age, sex, race, prenatal steroid exposure, and delivery mode. We collected conditioned media samples before and after a 6-h in vitro activation of naive CD4+ T lymphocytes with soluble staphylococcal enterotoxin B and anti-CD28. We analyzed samples by ultraperformance liquid chromatography ion mobility-mass spectrometry. We determined the impact of HCA on the CD4+ T lymphocyte exometabolome and identified potential biomarker metabolites by multivariate statistical analyses. We discovered that: 1) CD4+ T lymphocytes exposed to HCA exhibit divergent exometabolomic profiles in both naive and activated states; 2) ∼30% of detected metabolites differentially expressed in response to activation were unique to HCA-positive CD4+ T lymphocytes; 3) metabolic pathways associated with glutathione detoxification and tryptophan degradation were altered in HCA-positive CD4+ T lymphocytes; and 4) flow cytometry and cytokine analyses suggested a bias toward a TH1-biased immune response in HCA-positive samples. HCA exposure primes the neonatal adaptive immune processes by inducing changes to the exometabolomic profile of fetal CD4+ T lymphocytes. These exometabolomic changes may link HCA exposure to TH1 polarization of the neonatal adaptive immune response.

Real-time cellular exometabolome analysis with a microfluidic-mass spectrometry platform.

To address the challenges of tracking the multitude of signaling molecules and metabolites that is the basis of biological complexity, we describe a strategy to expand the analytical techniques for dynamic systems biology. Using microfluidics, online desalting, and mass spectrometry technologies, we constructed and validated a platform well suited for sampling the cellular microenvironment with high temporal resolution. Our platform achieves success in: automated cellular stimulation and microenvironment control; reduced non-specific adsorption to polydimethylsiloxane due to surface passivation; real-time online sample collection; near real-time sample preparation for salt removal; and real-time online mass spectrometry. When compared against the benchmark of "in-culture" experiments combined with ultraperformance liquid chromatography-electrospray ionization-ion mobility-mass spectrometry (UPLC-ESI-IM-MS), our platform alleviates the volume challenge issues caused by dilution of autocrine and paracrine signaling and dramatically reduces sample preparation and data collection time, while reducing undesirable external influence from various manual methods of manipulating cells and media (e.g., cell centrifugation). To validate this system biologically, we focused on cellular responses of Jurkat T cells to microenvironmental stimuli. Application of these stimuli, in conjunction with the cell's metabolic processes, results in changes in consumption of nutrients and secretion of biomolecules (collectively, the exometabolome), which enable communication with other cells or tissues and elimination of waste. Naïve and experienced T-cell metabolism of cocaine is used as an exemplary system to confirm the platform's capability, highlight its potential for metabolite discovery applications, and explore immunological memory of T-cell drug exposure. Our platform proved capable of detecting metabolomic variations between naïve and experienced Jurkat T cells and highlights the dynamics of the exometabolome over time. Upregulation of the cocaine metabolite, benzoylecgonine, was noted in experienced T cells, indicating potential cellular memory of cocaine exposure. These metabolomics distinctions were absent from the analogous, traditional "in-culture" UPLC-ESI-IM-MS experiment, further demonstrating this platform's capabilities.

Systems-level view of cocaine addiction: the interconnection of the immune and nervous systems.

The human body is a complex assembly of physiological systems designed to manage the multidirectional transport of both information and nutrients. An intricate interplay between the nervous, circulatory, and secretory systems is therefore necessary to sustain life, allow delivery of nutrients and therapeutic drugs, and eliminate metabolic waste products and toxins. These systems also provide vulnerable routes for modification by substances of abuse. Addictive substances are, by definition, neurologically active, but as they and their metabolites are spread throughout the body via the nervous, circulatory, respiratory and digestive systems, there is abundant opportunity for interaction with numerous cell and tissue types. Cocaine is one such substance that exerts a broad physiological effect. While a great deal of the research concerning addiction has addressed the neurological effects of cocaine use, only a few studies have been aimed at delineating the role that cocaine plays in various body systems. In this paper, we probe the current research regarding cocaine and the immune system, and map a systems-level view to outline a broader perspective of the biological response to cocaine. Specifically, our overview of the neurological and immunomodulatory effects of the drug will allow a broader perspective of the biological response to cocaine. The focus of this review is on the connection between the nervous and immune systems and the role this connection plays in the long-term complications of cocaine use. By describing the multiplicity of these connections, we hope to inspire detailed investigations into the immunological interplay in cocaine addiction.

Phenotypic mapping of metabolic profiles using self-organizing maps of high-dimensional mass spectrometry data.

A metabolic system is composed of inherently interconnected metabolic precursors, intermediates, and products. The analysis of untargeted metabolomics data has conventionally been performed through the use of comparative statistics or multivariate statistical analysis-based approaches; however, each falls short in representing the related nature of metabolic perturbations. Herein, we describe a complementary method for the analysis of large metabolite inventories using a data-driven approach based upon a self-organizing map algorithm. This workflow allows for the unsupervised clustering, and subsequent prioritization of, correlated features through Gestalt comparisons of metabolic heat maps. We describe this methodology in detail, including a comparison to conventional metabolomics approaches, and demonstrate the application of this method to the analysis of the metabolic repercussions of prolonged cocaine exposure in rat sera profiles.

Engineering challenges for instrumenting and controlling integrated organ-on-chip systems.

The sophistication and success of recently reported microfabricated organs-on-chips and human organ constructs have made it possible to design scaled and interconnected organ systems that may significantly augment the current drug development pipeline and lead to advances in systems biology. Physiologically realistic live microHuman (µHu) and milliHuman (mHu) systems operating for weeks to months present exciting and important engineering challenges such as determining the appropriate size for each organ to ensure appropriate relative organ functional activity, achieving appropriate cell density, providing the requisite universal perfusion media, sensing the breadth of physiological responses, and maintaining stable control of the entire system, while maintaining fluid scaling that consists of ~5 mL for the mHu and ~5 µL for the µHu. We believe that successful mHu and µHu systems for drug development and systems biology will require low-volume microdevices that support chemical signaling, microfabricated pumps, valves and microformulators, automated optical microscopy, electrochemical sensors for rapid metabolic assessment, ion mobility-mass spectrometry for real-time molecular analysis, advanced bioinformatics, and machine learning algorithms for automated model inference and integrated electronic control. Toward this goal, we are building functional prototype components and are working toward top-down system integration.

A dual-column solid phase extraction strategy for online collection and preparation of continuously flowing effluent streams for mass spectrometry.

Current desalination techniques for mass spectrometry-based protocols are problematic for performing temporal response studies where increased temporal resolution requires small samples and faster sampling frequencies, which greatly increases the number of samples and sample preparation time. These challenges are pertinent to cellular dynamics experiments, where it is important to sample the biological system frequently and with as little sample waste as possible. To address these needs, we present a dual-column online solid phase extraction (SPE) approach capable of preconcentrating and preparing a constantly perfusing sample stream, with minimal to no sample loss. This strategy is evaluated for use in microfluidic bioreactor studies specifically aimed at characterizing suitable sample flow rates, temporal resolving power, and analyte concentrations. In this work, we demonstrate that this strategy may be used for flow rates as low as 500 nL/min, with temporal resolving power on the order of 3 min, with analyte loadings ranging from femtomoles to picomoles for metabolites. Under these conditions, recoveries of ca. 80% are obtained even at femtomole loadings.