Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS1) and in Silico Peptide Mass Libraries

Over the past decade, modern methods of MS (MS) have emerged that allow reliable, fast and cost-effective identification of pathogenic microorganisms. Although MALDI-TOF MS has already revolutionized the way microorganisms are identified, recent years have witnessed also substantial progress in the development of liquid chromatography (LC)-MS based proteomics for microbiological applications. For example, LC-tandem MS (LC-MS2) has been proposed for microbial characterization by means of multiple discriminative peptides that enable identification at the species, or sometimes at the strain level. However, such investigations can be laborious and time-consuming, especially if the experimental LC-MS2 data are tested against sequence databases covering a broad panel of different microbiological taxa. In this proof of concept study, we present an alternative bottom-up proteomics method for microbial identification. The proposed approach involves efficient extraction of proteins from cultivated microbial cells, digestion by trypsin and LC–MS measurements. Peptide masses are then extracted from MS1 data and systematically tested against an in silico library of all possible peptide mass data compiled in-house. The library has been computed from the UniProt Knowledgebase covering Swiss-Prot and TrEMBL databases and comprises more than 12,000 strain-specific in silico profiles, each containing tens of thousands of peptide mass entries. Identification analysis involves computation of score values derived from correlation coefficients between experimental and strain-specific in silico peptide mass profiles and compilation of score ranking lists. The taxonomic positions of the microbial samples are then determined by using the best-matching database entries. The suggested method is computationally efficient – less than 2 mins per sample - and has been successfully tested by a test set of 39 LC-MS1 peak lists obtained from 19 different microbial pathogens. The proposed method is rapid, simple and automatable and we foresee wide application potential for future microbiological applications.

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Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS1) and in silico Peptide Mass Data

10.1101/870089 ◽

2019 ◽

Cited By ~ 1

Author(s):

Peter Lasch ◽

Andy Schneider ◽

Christian Blumenscheit ◽

Joerg Doellinger

Keyword(s):

Mass Spectrometry ◽

Liquid Chromatography ◽

In Silico ◽

Cost Effective ◽

Microbial Pathogens ◽

Computationally Efficient ◽

Microbial Identification ◽

Mass Data ◽

Peptide Mass ◽

Substantial Progress

1.ABSTRACTOver the past decade, modern methods of mass spectrometry (MS) have emerged that allow reliable, fast and cost-effective identification of pathogenic microorganisms. While MALDI-TOF MS has already revolutionized the way microorganisms are identified, recent years have witnessed also substantial progress in the development of liquid chromatography (LC)-MS based proteomics for microbiological applications. For example, LC-tandem mass spectrometry (LC-MS2) has been proposed for microbial characterization by means of multiple discriminative peptides that enable identification at the species, or sometimes at the strain level. However, such investigations can be very time-consuming, especially if the experimental LC-MS2 data are tested against sequence databases covering a broad panel of different microbiological taxa.In this proof of concept study, we present an alternative bottom-up proteomics method for microbial identification. The proposed approach involves efficient extraction of proteins from cultivated microbial cells, digestion by trypsin and LC-MS measurements. MS1 data are then extracted and systematically tested against an in silico library of peptide mass data compiled in house. The library has been computed from the UniProt Knowledgebase Swiss-Prot and TrEMBL databases and comprises more than 12,000 strain-specific in silico profiles, each containing tens of thousands of peptide mass entries. Identification analysis involves computation of score values derived from spectral distances between experimental and in silico peptide mass data and compilation of score ranking lists. The taxonomic positions of the microbial samples are then determined by using the best-matching database entries. The suggested method is computationally efficient – less than two minutes per sample - and has been successfully tested by a set of 19 different microbial pathogens. The approach is rapid, accurate and automatable and holds great potential for future microbiological applications.

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Flavonoid Quantification in Onion by Spectrophotometric and High Performance Liquid Chromatography Analysis

HortScience ◽

10.21273/hortsci.37.4.682 ◽

2002 ◽

Vol 37 (4) ◽

pp. 682-685 ◽

Cited By ~ 40

Author(s):

Kevin A. Lombard ◽

Emmanuel Geoffriau ◽

Ellen Peffley

Keyword(s):

High Performance Liquid Chromatography ◽

Liquid Chromatography ◽

High Performance ◽

Hplc Analysis ◽

Correlation Coefficients ◽

Cost Effective ◽

Chromatography Analysis ◽

Cost Effective Method ◽

Performance Liquid Chromatography Analysis

Direct spectrophotometric determination of quercetin content in onions (Allium cepa L.) was investigated as a possible alternative to high-performance liquid chromatography (HPLC) analysis. Quercetin content in five onion varieties was monitored at 362 nm and quantified using simple spectrophotometric and HPLC methods. HPLC revealed that 3,4'-Qdg and 4'-Qmg comprised up to 93% of total flavonol content detected in the studied varieties. These major quercetin conjugates combined (3,4'-Qdg + 4'-Qmg) and total flavonol conjugates quantified by HPLC correlated closely with spectrophotometer values. Correlation coefficients were 0.96 (P < 0.0001) for 3,4'-Qdg + 4'-Qmg and 0.97 (P < 0.0001) for total flavonol conjugates in onion. Simple spectrophotometric procedure proved to be a valid, efficient, and cost-effective method for the quantification of total quercetin in onion. Chemical names used: quercetin-3,4'-O-diglucoside (3,4'-Qdg); quercetin-4'-O-glucoside (4'-Qmg).

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The ENmix DNA methylation analysis pipeline for Illumina BeadChip and comparisons with seven other preprocessing pipelines

Clinical Epigenetics ◽

10.1186/s13148-021-01207-1 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Zongli Xu ◽

Liang Niu ◽

Jack A. Taylor

Keyword(s):

Dna Methylation ◽

Intraclass Correlation ◽

Correlation Coefficients ◽

Cost Effective ◽

Data Preprocessing ◽

Absolute Difference ◽

Computationally Efficient ◽

Methylation Array ◽

Raw Data ◽

Dna Methylation Array

Abstract Background Illumina DNA methylation arrays are high-throughput platforms for cost-effective genome-wide profiling of individual CpGs. Experimental and technical factors introduce appreciable measurement variation, some of which can be mitigated by careful “preprocessing” of raw data. Methods Here we describe the ENmix preprocessing pipeline and compare it to a set of seven published alternative pipelines (ChAMP, Illumina, SWAN, Funnorm, Noob, wateRmelon, and RnBeads). We use two large sets of duplicate sample measurements with 450 K and EPIC arrays, along with mixtures of isogenic methylated and unmethylated cell line DNA to compare raw data and that preprocessed via different pipelines. Results Our evaluations show that the ENmix pipeline performs the best with significantly higher correlation and lower absolute difference between duplicate pairs, higher intraclass correlation coefficients (ICC) and smaller deviations from expected methylation level in mixture experiments. In addition to the pipeline function, ENmix software provides an integrated set of functions for reading in raw data files from mouse and human arrays, quality control, data preprocessing, visualization, detection of differentially methylated regions (DMRs), estimation of cell type proportions, and calculation of methylation age clocks. ENmix is computationally efficient, flexible and allows parallel computing. To facilitate further evaluations, we make all datasets and evaluation code publicly available. Conclusion Careful selection of robust data preprocessing methods is critical for DNA methylation array studies. ENmix outperformed other pipelines in our evaluations to minimize experimental variation and to improve data quality and study power.

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In the Quest for a Stable Triplet State in Small Polyaromatic Hydrocarbons : An In-Silico Tool for Rational Design and Prediction

10.26434/chemrxiv.8143274.v1 ◽

2019 ◽

Author(s):

Madhumita Rano ◽

Sumanta K Ghosh ◽

Debashree Ghosh

Keyword(s):

Triplet State ◽

Small Molecules ◽

In Silico ◽

Qualitative Agreement ◽

Rational Design ◽

Polyaromatic Hydrocarbons ◽

Spin Hamiltonian ◽

Spin Frustration ◽

Computationally Efficient ◽

High Level

<div>Combining the roles of spin frustration and geometry of odd and even numbered rings in polyaromatic hydrocarbons (PAHs), we design small molecules that show exceedingly small singlet-triplet gaps and stable triplet ground states. Furthermore, a computationally efficient protocol with a model spin Hamiltonian is shown to be capable of qualitative agreement with respect to high level multireference calculations and therefore, can be used for fast molecular discovery and screening.</div>

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Corncob Waste Based Adsorbent for Solid Phase Extraction of Tartrazine in Carbonated Drinks and Analytical Method using Ultra Performance Liquid Chromatography-Mass Spectrometry

Current Analytical Chemistry ◽

10.2174/1573411015666191028113257 ◽

2020 ◽

Vol 16 (7) ◽

pp. 924-932

Author(s):

Yasmeen Mutlaq Ghazi Al Shamari ◽

Saikh Mohammad Wabaidur ◽

Abdulrahman Abdullah Alwarthan ◽

Moonis Ali Khan ◽

Masoom Raza Siddiqui

Keyword(s):

Mass Spectrometry ◽

Liquid Chromatography ◽

Solid Phase Extraction ◽

Solid Phase ◽

Cost Effective ◽

Ultra Performance Liquid Chromatography ◽

Phase Extraction ◽

Food Dye ◽

Hyphenated Technique

Background : A new method has been developed for the determination of food dye tartrazine in soft drinks. Tartrazine is determined by hyphenated technique Ultra Performance Liquid Chromatography coupled with Mass spectrometry. The solid-phase extraction was used for the extraction of tartrazine. Methods: For the LC-MS analysis of tartrazine acetonitrile, water (80:20) was used as a mobile phase whereas, the C-18 column was selected as the stationary phase. The chromatographic run was allowed for 1 min. The adsorbent of the solid-phase extraction was synthesized from the waste corn cob. Results: Method found to be linear in the range of 0.1 mg L-1 - 10 mg L-1, limits of detection and quantitation were found to be 0.0165 mgL-1 and 0.055 mgL-1, respectively. Tartrazine, in the real sample, was found to be 20.39 mgL-1 and 83.26 mgL-1. Conclusion: The developed UPLC-MS method is rapid, simple, precise and can be used for the quantitative analysis of tartrazine. The solid-phase extraction also involves a cost-effective procedure for extraction as it does not involve the commercial cartridge.

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Reproducibility and relative validity of a semi-quantitative food frequency questionnaire for the Chinese lactating mothers

Nutrition Journal ◽

10.1186/s12937-021-00678-5 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Ye Ding ◽

Fang Li ◽

Ping Hu ◽

Mei Ye ◽

Fangping Xu ◽

...

Keyword(s):

Food Frequency Questionnaire ◽

Dietary Assessment ◽

Correlation Coefficients ◽

Cost Effective ◽

Assessment Method ◽

Food Frequency ◽

Relative Validity ◽

Lactating Mothers ◽

Dietary Record ◽

Spearman’S Correlation

Abstract Background The dietary nutritional status of the lactating mothers is related to maternal health and has a significant impact on the growth and development of infants through the secretion of breast milk. The food frequency questionnaire (FFQ) is the most cost-effective dietary assessment method that can help obtain information on the usual dietary pattern of participants. Until now, the FFQs have been used for different populations in China, but there are few FFQs available for the lactating mothers. We aimed to develop a semi-quantitative, 156-item FFQ for the Chinese lactating mothers, and evaluate its reproducibility and relative validity. Methods A total of 112 lactating mothers completed two FFQs and one 3-d dietary record (3DR). The first FFQ (FFQ1) was conducted during postpartum at 60–65 days and the second FFQ (FFQ2) during subsequent follow-up at 5 weeks. The 3DR was completed with portion sizes assessed using photographs taken by the respondent before and after eating (instant photography) 1 week after FFQ1. Results For reproducibility, the Spearman’s correlation coefficients for food ranged from 0.34 to 0.68, and for nutrients from 0.25 to 0.61. Meanwhile, the intra-class correlation coefficients for food ranged from 0.48 to 0.87, and for nutrients from 0.27 to 0.70. For relative validity, the Spearman’s correlation coefficients for food ranged from 0.32 to 0.56, and for nutrients from 0.23 to 0.72. The energy-adjusted coefficients for food ranged from 0.26 to 0.55, and for nutrients from 0.22 to 0.47. Moreover, the de-attenuation coefficients for food ranged from 0.34 to 0.67, and for nutrients from 0.28 to 0.77. The Bland-Altman plots also showed reasonably acceptable agreement between the two methods. Conclusions This FFQ is a reasonably reproducible and a relative valid tool for assessing dietary intake of the Chinese lactating mothers.

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Pimenta dioica and Pimenta racemosa: GC-based metabolomics for the assessment of seasonal and organs variation in their volatile components, in silico and in vitro cytotoxic activity estimation

Food & Function ◽

10.1039/d1fo00408e ◽

2021 ◽

Author(s):

Fadia S. Youssef ◽

Rola Labib ◽

A. Gad Haidy ◽

Safaa Eid ◽

Mohamed Lotfy Ashour ◽

...

Keyword(s):

Liquid Chromatography ◽

Cytotoxic Activity ◽

In Silico ◽

Volatile Components ◽

Gas Liquid Chromatography ◽

Four Seasons ◽

Pimenta Racemosa ◽

Pimenta Dioica ◽

Activity Estimation

Volatile constituents isolated from stems (S) and leaves (L) of Pimenta dioica (PD) and Pimenta racemosa (PR) during the four seasons were analyzed using GLC/FID (Gas liquid chromatography – flame...

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Single-Run Separation and Quantification of 14 Cannabinoids Using Capillary Electrophoresis

Separations ◽

10.3390/separations8030030 ◽

2021 ◽

Vol 8 (3) ◽

pp. 30

Author(s):

Emil A. Zaripov ◽

Tiah Lee ◽

Yuchu Dou ◽

Cory S. Harris ◽

Artem Egorov ◽

...

Keyword(s):

High Pressure ◽

Capillary Electrophoresis ◽

Liquid Chromatography ◽

Sodium Hydroxide ◽

Limit Of Detection ◽

Cost Effective ◽

Uv Detector ◽

Good Separation ◽

Method Performance ◽

Cost Effective Alternative

Quantification of major cannabinoids in cannabis products is normally performed using high-pressure liquid chromatography (HPLC)-based methods. We propose a cost-effective alternative method that successfully separates and quantifies 14 cannabinoids in a single run using capillary electrophoresis (CE) coupled with a UV detector in 18 min. The separation is carried out in 60% acetonitrile in the presence of 6.5 mM sodium hydroxide and 25 µM β-cyclodextrin, resulting in good separation of cannabinoids. Our CE method demonstrated the limit of detection between 1.2–1.8 µg/mL, with the linear range reaching up to 50 µg/mL. We validated the method performance by testing a plant extract and quantifying cannabinoid content. This method is the first to separate 14 cannabinoids in one run using a CE system with UV detection.

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