We use shotgun proteomics to identify biomarkers of diagnostic and prognostic value in individuals diagnosed with amyotrophic lateral sclerosis. Matched cerebrospinal and plasma fluids were subjected to abundant protein depletion and analyzed by nano-flow liquid chromatography high resolution tandem mass spectrometry. Label free quantitation was used to identify differential proteins between individuals with ALS (n = 33) and healthy controls (n = 30) in both fluids. In CSF, 118 (p-value < 0.05) and 27 proteins (q-value < 0.05) were identified as significantly altered between ALS and controls. In plasma, 20 (p-value < 0.05) and 0 (q-value < 0.05) proteins were identified as significantly altered between ALS and controls. Proteins involved in complement activation, acute phase response and retinoid signaling pathways were significantly enriched in the CSF from ALS patients. Subsequently various machine learning methods were evaluated for disease classification using a repeated Monte Carlo cross-validation approach. A linear discriminant analysis model achieved a median area under the receiver operating characteristic curve of 0.94 with an interquartile range of 0.88–1.0. Three proteins composed a prognostic model (p = 5e-4) that explained 49% of the variation in the ALS-FRS scores. Finally we investigated the specificity of two promising proteins from our discovery data set, chitinase-3 like 1 protein and alpha-1-antichymotrypsin, using targeted proteomics in a separate set of CSF samples derived from individuals diagnosed with ALS (n = 11) and other neurological diseases (n = 15). These results demonstrate the potential of a panel of targeted proteins for objective measurements of clinical value in ALS.

Opioid testing represents a dominant share of the market in pain management clinical testing facilities. Testing of this drug class in oral fluid (OF) has begun to rise in popularity. OF analysis has traditionally required extensive clean-up protocols and sample concentration, which can be avoided. This work highlights the use of a fast, ‘dilute-and-shoot’ method that performs no considerable sample manipulation. A quantitative method for the determination of eight common opioids and associated metabolites (codeine, morphine, hydrocodone, hydromorphone, norhydrocodone, oxycodone, noroxycodone and oxymorphone) in OF is described herein. OF sample is diluted 10-fold in methanol/water and then analyzed using an Agilent chromatographic stack coupled with an AB SCIEX 4500. The method has a 2.2-min LC gradient and a cycle time of 2.9 min. In contrast to most published methods of this particular type, this method uses no sample clean-up or concentration and has a considerably faster LC gradient, making it ideal for very high-throughput laboratories. Importantly, the method requires only 100 μL of sample and is diluted 10-fold prior to injection to help with instrument viability. Baseline separation of all isobaric opioids listed above was achieved on a phenyl-hexyl column. The validated calibration range for this method is 2.5–1,000 ng/mL. This ‘dilute-and-shoot’ method removes the unnecessary, costly and time-consuming extraction steps found in traditional methods and still surpasses all analytical requirements.

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.

Extracellular matrix (ECM) is a complex structure composed of bioactive molecules representative of the local tissue microenvironment. Decellularized ECM biomaterials harness these biomolecules for regenerative medicine applications. One potential therapeutic application is the use of vocal fold (VF) specific ECM to restore the VFs after injury. ECM scaffolds are derived through a process of decellularization, which aims to remove unwanted immunogenic biomolecules (e.g. DNA) while preserving the composition of the ECM. The effectiveness of the decellularization is typically assessed at the end by quantifying ECM attributes such as final dsDNA content. However, batch-to-batch variability in ECM manufacturing remains a significant challenge for the standardization, cost-effectiveness, and scale-up process. The limited number of tools available for in-process control heavily restricts the uncovering of the correlations between decellularization process parameters and ECM attributes. In this study, we developed a technique applicable to both the classical batch method and semi-continuous decellularization systems to trace the decellularization of two laryngeal tissues in real-time. We hypothesize that monitoring the bioreactor’s effluent absorbance at 260 nm as a function of time will provide a representative DNA release profile from the tissue and thus allow for process optimization. The DNA release profiles were obtained for laryngeal tissues and were successfully used to optimize the derivation of VF lamina propria-ECM (auVF-ECM) hydrogels. This hydrogel had comparable rheological properties to commonly used biomaterials to treat VF injuries. Also, the auVF-ECM hydrogel promoted the down-regulation of CCR7 by THP-1 macrophages upon lipopolysaccharide stimulation in vitro suggesting some anti-inflammatory properties. The results show that absorbance profiles are a good representation of DNA removal during the decellularization process thus providing an important tool to optimize future protocols.

From 1980 to 2017, Wilmington, North Carolina (NC), residents unknowingly consumed high levels of PFAS through drinking water. Some of these PFAS are expected to have short biological half-lives, and current biological sampling will miss these exposures. To assess historical PFAS exposures, we (1) determined PFAS levels in serum samples of Wilmington, NC residents obtained during the years 2010-2016, (2) examined temporal trends of serum PFAS over this period, and (3) associated serum PFAS levels with PFAS concentrations in drinking water. We quantified 56 PFAS, including ultrashort-chain PFAS, in 119 adult human serum samples and 47 PFAS in water samples from 2017. Twenty PFAS were detected in >50% of serum samples; perfluoromethoxyacetic acid (PFMOAA) and trifluoroacetic acid (TFA) exhibited the highest median concentrations (PFMOAA: 42 ng/mL; TFA: 17 ng/mL). PFMOAA and TFA were also the dominant PFAS in Wilmington drinking water, accounting for 95% of quantifiable PFAS. The serum-to-water ratio was linearly correlated with "effective" PFAS chain length, indicating that PFAS with longer chain length and a sulfonic acid group are more bioaccumulative. While chain length is important for bioaccumulation, this study highlights that exposures to high concentrations of ultrashort-chain PFAS in drinking water contribute to their dominance in human serum.