The Future of Proteomics is Up in the Air: Can Ion Mobility Replace Liquid Chromatography for High Throughput Proteomics?

The coevolution of liquid chromatography (LC) with mass spectrometry (MS) has shaped contemporary proteomics. LC hyphenated to MS now enables quantification of more than 10,000 proteins in a single injection, a number that likely represents most proteins in specific human cells or tissues. Separations by ion mobility spectrometry (IMS) have recently emerged to complement LC and further improve the depth of proteomics. Given the theoretical advantages in speed and robustness of IMS in comparison to LC, we envision that ongoing improvements to IMS paired with MS may eventually make LC obsolete, especially when combined with targeted or simplified analyses, such as rapid clinical proteomics analysis of defined biomarker panels. In this perspective, we describe the need for faster analysis that might drive this transition, the current state of direct infusion proteomics, and discuss some technical challenges that must be overcome to fully complete the transition to entirely gas phase proteomics.

A Complete Workflow for High Throughput Human Single Skeletal Muscle Fiber Proteomics.

Skeletal muscle is a major regulatory tissue of whole-body metabolism and is composed of a diverse mixture of cell (fiber) types. Aging and several diseases differentially affect the various fiber types, and therefore, investigating the changes in the proteome in a fiber-type specific manner is essential. Recent breakthroughs in isolated single muscle fiber proteomics have started to reveal heterogeneity among fibers. However, existing procedures are slow and laborious, requiring 2 h of mass spectrometry time per single muscle fiber; 50 fibers would take approximately 4 days to analyze. Thus, to capture the high variability in fibers both within and between individuals requires advancements in high throughput single muscle fiber proteomics. Here we use a single cell proteomics method to enable quantification of single muscle fiber proteomes in 15 min total instrument time. As proof of concept, we present data from 53 isolated skeletal muscle fibers obtained from two healthy individuals analyzed in 13.25 h. Adapting single cell data analysis techniques to integrate the data, we can reliably separate type 1 and 2A fibers. Ninety-four proteins were statistically different between clusters indicating alteration of proteins involved in fatty acid oxidation, oxidative phosphorylation, and muscle structure and contractile function. Our results indicate that this method is significantly faster than prior single fiber methods in both data collection and sample preparation while maintaining sufficient proteome depth. We anticipate this assay will enable future studies of single muscle fibers across hundreds of individuals, which has not been possible previously due to limitations in throughput.

High-Throughput Single-Cell Proteomic Analysis of Organ-Derived Heterogeneous Cell Populations by Nanoflow Dual-Trap Single-Column Liquid Chromatography.

Identification and proteomic characterization of rare cell types within complex organ-derived cell mixtures is best accomplished by label-free quantitative mass spectrometry. High throughput is required to rapidly survey hundreds to thousands of individual cells to adequately represent rare populations. Here we present parallelized nanoflow dual-trap single-column liquid chromatography (nanoDTSC) operating at 15 min of total run time per cell with peptides quantified over 11.5 min using standard commercial components, thus offering an accessible and efficient LC solution to analyze 96 single cells per day. At this throughput, nanoDTSC quantified over 1000 proteins in individual cardiomyocytes and heterogeneous populations of single cells from the aorta.

Complete Workflow for High Throughput Human Single Skeletal Muscle Fiber Proteomics.

Skeletal muscle is a major regulatory tissue of whole-body metabolism and is composed of a diverse mixture of cell (fiber) types. Aging and several diseases differentially affect the various fiber types, and therefore, investigating the changes in the proteome in a fiber-type specific manner is essential. Recent breakthroughs in isolated single muscle fiber proteomics have started to reveal heterogeneity among fibers. However, existing procedures are slow and laborious requiring two hours of mass spectrometry time per single muscle fiber; 50 fibers would take approximately four days to analyze. Thus, to capture the high variability in fibers both within and between individuals requires advancements in high throughput single muscle fiber proteomics. Here we use a single cell proteomics method to enable quantification of single muscle fiber proteomes in 15 minutes total instrument time. As proof of concept, we present data from 53 isolated skeletal muscle fibers obtained from two healthy individuals analyzed in 13.25 hours. Adapting single cell data analysis techniques to integrate the data, we can reliably separate type 1 and 2A fibers. Sixty-five proteins were statistically different between clusters indicating alteration of proteins involved in fatty acid oxidation, muscle structure and regulation. Our results indicate that this method is significantly faster than prior single fiber methods in both data collection and sample preparation while maintaining sufficient proteome depth. We anticipate this assay will enable future studies of single muscle fibers across hundreds of individuals, which has not been possible previously due to limitations in throughput.

High Throughput Single Cell Proteomic Analysis of Organ Derived Heterogeneous Cell Populations by Nanoflow Dual Trap Single Column Liquid Chromatography.

Identification and proteomic characterization of rare cell types within complex organ derived cell mixtures is best accomplished by label-free quantitative mass spectrometry. High throughput is required to rapidly survey hundreds to thousands of individual cells to adequately represent rare populations. Here we present parallelized nanoflow dual-trap single-column liquid chromatography (nanoDTSC) operating at 15 minutes of total run time per cell with peptides quantified over 11.5 minutes using standard commercial components, thus offering an accessible and efficient LC solution to analyze 96 single-cells per day. At this throughput, nanoDTSC quantified over 1,000 proteins in individual cardiomyocytes and heterogenous populations of single cells from aorta.

Parallelization with Dual-Trap Single-Column Configuration Maximizes Throughput of Proteomic Analysis.

Proteomic analysis on the scale that captures population and biological heterogeneity over hundreds to thousands of samples requires rapid mass spectrometry methods, which maximize instrument utilization (IU) and proteome coverage while maintaining precise and reproducible quantification. To achieve this, a short liquid chromatography gradient paired to rapid mass spectrometry data acquisition can be used to reproducibly quantify a moderate set of analytes. High-throughput profiling at a limited depth is becoming an increasingly utilized strategy for tackling large sample sets but the time spent on loading the sample, flushing the column(s), and re-equilibrating the system reduces the ratio of meaningful data acquired to total operation time and IU. The dual-trap single-column configuration (DTSC) presented here maximizes IU in rapid analysis (15 min per sample) of blood and cell lysates by parallelizing trap column cleaning and sample loading and desalting with the analysis of the previous sample. We achieved 90% IU in low microflow (9.5 µL/min) analysis of blood while reproducibly quantifying 300-400 proteins and over 6000 precursor ions. The same IU was achieved for cell lysates and over 4000 proteins (3000 at CV below 20%) and 40,000 precursor ions were quantified at a rate of 15 min/sample. Thus, DTSC enables high-throughput epidemiological blood-based biomarker cohort studies and cell-based perturbation screening.

Real-time prediction and avoidance of secondary crashes under unexpected traffic congestion.

According to the Federal Highway Administration, nonrecurring congestion contributes to nearly half of the overall congestion. Temporal disruptions impact the effective use of the complete roadway, due to speed reduction and rubbernecking resulting from primary incidents that in turn provoke secondary incidents. There is an additional reduction of discharge flow caused by secondary incident that significantly increases total delay. Therefore, it is important to sequentially predict the probability of secondary incidents and develop appropriate countermeasures to reduce the associated risk. Advanced computing techniques were used to easily understand and reliably predict secondary incident occurrences that have low sample mean and a small sample size. The likelihood of a secondary incident was sequentially predicted from the point of incident response to the eventual road clearance. The quality of predictions improved with the availability of additional information. The prediction performance of the principled Bayesian learning approach to neural networks (bnn) was compared to the Stochastic Gradient Boosted Decision Trees (gbdt). A pedagogical rule extraction approach, trepan, which extracts comprehensible rules from the neural networks, improved the ability to understand secondary incidents in a simplified manner. With an acceptable accuracy, gbdt is a useful tool that presents the relative importance of the predictor variables. Unexpected traffic congestion incurred by an incident is a dominant causative factor for the occurrence of secondary incidents at different stages of incident clearance. This symbolic description represents a series of decisions that may assist emergency operators by improving their decision-making capabilities. Analyzing causes and effects of traffic incidents helps traffic operators develop incident-specific strategic plans for prompt emergency response and clearance. Application of the model in connected vehicle environments will help drivers receive proactive corrective feedback before a crash. The proposed methodology can be used to alert drivers about potential highway conditions and may increase the drivers' awareness of potential events when no rerouting is possible, optimal or otherwise.

Erratum to 'Seasonal habitat suitability modeling and factors affecting the distribution of Asian Houbara in East Iran'.

[This corrects the article DOI: 10.1016/j.heliyon.2016.e00142.].

Results of an interlaboratory comparison of analytical methods for contaminants of emerging concern in water.

An evaluation of existing analytical methods used to measure contaminants of emerging concern (CECs) was performed through an interlaboratory comparison involving 25 research and commercial laboratories. In total, 52 methods were used in the single-blind study to determine method accuracy and comparability for 22 target compounds, including pharmaceuticals, personal care products, and steroid hormones, all at ng/L levels in surface and drinking water. Method biases ranged from <10% to well over 100% in both matrixes, suggesting that while some methods are accurate, others can be considerably inaccurate. In addition, the number and degree of outliers identified suggest a high degree of variability may be present between methods currently in use. Three compounds, ciprofloxacin, 4-nonylphenol (NP), and 4-tert-octylphenol (OP), were especially difficult to measure accurately. While most compounds had overall false positive rates of ≤5%, bisphenol A, caffeine, NP, OP, and triclosan had false positive rates >15%. In addition, some methods reported false positives for 17ß-estradiol and 17α-ethynylestradiol in unspiked drinking water and deionized water, respectively, at levels higher than published predicted no-effect concentrations for these compounds in the environment. False negative rates were also generally <5%; however, rates were higher for the steroid hormones and some of the more challenging compounds, such as ciprofloxacin. The elevated false positive/negative rates of some analytes emphasize the susceptibility of many current methods to blank contamination, misinterpretation of background interferences, and/or inappropriate setting of detection/quantification levels for analysis at low ng/L levels. The results of both comparisons were collectively assessed to identify parameters that resulted in the best overall method performance. Liquid chromatography-tandem mass spectrometry coupled with the calibration technique of isotope dilution were able to accurately quantify most compounds with an average bias of <10% for both matrixes. These findings suggest that this method of analysis is suitable at environmentally relevant levels for most of the compounds studied. This work underscores the need for robust, standardized analytical methods for CECs to improve data quality, increase comparability between studies, and help reduce false positive and false negative rates.

Occurrence and suitability of sucralose as an indicator compound of wastewater loading to surface waters in urbanized regions.

Urban watersheds are susceptible to numerous pollutant sources and the identification of source-specific indicators can provide a beneficial tool in the identification and control of input loads, often times needed for a water body to achieve designated beneficial uses. Differentiation of wastewater flows from other urban wet weather flows is needed in order to more adequately address such environmental concerns as water body nutrient impairment and potable source water contamination. Anthropogenic compounds previously suggested as potential wastewater indicators include caffeine, carbamazepine, N,N-diethyl-meta-toluamide (DEET), gemfibrozil, primidone, sulfamethoxazole, and TCEP. This paper compares the suitability of a variety of anthropogenic compounds to sucralose, an artificial sweetener, as wastewater indicators by examining occurrence data for 85 trace organic compounds in samples of wastewater effluents, source waters with known wastewater point source inputs, and sources without known wastewater point source inputs. The findings statistically demonstrate the superior performance of sucralose as a potential indicator of domestic wastewater input in the U.S. While several compounds were detected in all of the wastewater effluent samples, only sucralose was consistently detected in the source waters with known wastewater discharges, absent in the sources without wastewater influence, and consistently present in septic samples. All of the other compounds were prone to either false negatives or false positives in the environment.

Determination of total chromium in environmental water samples.

It is often desirable to quantify both dissolved Cr(VI) and total Cr in samples accurately. Various protocols are now being utilized to quantify the amount of total chromium in natural waters and each of these has possible interferences. This study describes the shortcomings of each method when particulate iron is present in a water sample, and a more rigorous digestion protocol is tested. Data from bench studies as well as a field survey of 21 water utilities are presented. Additionally, field data from several hundred water utility samples are presented to illustrate the potential for incomplete recovery of total chromium using accepted protocols.