Improving peptide relative quantification in MALDI-TOF MS for biomarker assessment

Intracellular Amyloid-β Detection from Human Brain Sections Using a Microfluidic Immunoassay in Tandem with MALDI-MS

Alzheimer's disease (AD) currently affects more than 30 million people worldwide. The lack of understanding of AD's physiopathology limits the development of therapeutic and diagnostic tools. Soluble amyloid-β peptide (Aβ) oligomers that appear as intermediates along the Aβ aggregation into plaques are considered among the main AD neurotoxic species. Although a wealth of data are available about Aβ from in vitro and animal models, there is little known about intracellular Aβ in human brain cells, mainly due to the lack of technology to assess the intracellular protein content. The elucidation of the Aβ species in specific brain cell subpopulations can provide insight into the role of Aβ in AD and the neurotoxic mechanism involved. Here, we report a microfluidic immunoassay for in situ mass spectrometry analysis of intracellular Aβ species from archived human brain tissue. This approach comprises the selective laser dissection of individual pyramidal cell bodies from tissues, their transfer to the microfluidic platform for sample processing on-chip, and mass spectrometric characterization. As a proof-of-principle, we demonstrate the detection of intracellular Aβ species from as few as 20 human brain cells.

MIMAS: microfluidic platform in tandem with MALDI mass spectrometry for protein quantification from small cell ensembles

Understanding cell-to-cell variation at the molecular level provides relevant information about biological phenomena and is critical for clinical and biological research. Proteins carry important information not available from single-cell genomics and transcriptomics studies; however, due to the minute amount of proteins in single cells and the complexity of the proteome, quantitative protein analysis at the single-cell level remains challenging. Here, we report an integrated microfluidic platform in tandem with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for the detection and quantification of targeted proteins from small cell ensembles (> 10 cells). All necessary steps for the assay are integrated on-chip including cell lysis, protein immunocapture, tryptic digestion, and co-crystallization with the matrix solution for MALDI-MS analysis. We demonstrate that our approach is suitable for protein quantification by assessing the apoptotic protein Bcl-2 released from MCF-7 breast cancer cells, ranging from 26 to 223 cells lysed on-chip (8.75 nL wells). A limit of detection (LOD) of 11.22 nM was determined, equivalent to 5.91 × 10⁷ protein molecules per well. Additionally, the microfluidic platform design was further improved, establishing the successful quantification of Bcl-2 protein from MCF-7 cell ensembles ranging from 8 to 19 cells in 4 nL wells. The LOD in the smaller well designs for Bcl-2 resulted in 14.85 nM, equivalent to 3.57 × 10⁷ protein molecules per well. This work shows the capability of our approach to quantitatively assess proteins from cell lysate on the MIMAS platform for the first time. These results demonstrate our approach constitutes a promising tool for quantitative targeted protein analysis from small cell ensembles down to single cells, with the capability for multiplexing through parallelization and automation.

Detection of SARS-CoV-2 Infection in Human Nasopharyngeal Samples by Combining MALDI-TOF MS and Artificial Intelligence

The high infectivity of SARS-CoV-2 makes it essential to develop a rapid and accurate diagnostic test so that carriers can be isolated at an early stage. Viral RNA in nasopharyngeal samples by RT-PCR is currently considered the reference method although it is not recognized as a strong gold standard due to certain drawbacks. Here we develop a methodology combining the analysis of from human nasopharyngeal (NP) samples by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with the use of machine learning (ML). A total of 236 NP samples collected in two different viral transport media were analyzed with minimal sample preparation and the subsequent mass spectra data was used to build different ML models with two different techniques. The best model showed high performance in terms of accuracy, sensitivity and specificity, in all cases reaching values higher than 90%. Our results suggest that the analysis of NP samples by MALDI-TOF MS and ML is a simple, safe, fast and economic diagnostic test for COVID-19.

Expression, purification and identification of isotope-labeled recombinant cystatin C protein in Escheichia coli intended for absolute quantification using isotope dilution mass spectrometry

Isotope-labeled proteins are expected to be used as internal standard proteins in the field of protein quantification by isotope dilution mass spectrometry (ID/MS). To achieve the absolute quantification of Cystatin C (Cys C) based on ID/MS, we aims to obtain ¹⁵N isotope-labeled recombinant Cys C (¹⁵N-Cys C) protein. Firstly, the Cys C gene was optimized based on the preferred codons of Escherichia coli, and inserted into the pET-28a(+) expression plasmid. Then, the plasmid was transformed into TOP10 and BL21 strains, and ¹⁵N-Cys C was expressed in M9 medium using ¹⁵N as the only nitrogen source. ¹⁵N-Cys C was detected by SDS-PAGE, protein immunoblotting and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). The characteristic peptides obtained from ¹⁵N-Cys C were analyzed by a Q Exactive Plus MS system. Results showed that 53.06% of the codons were optimized. The codon adaptation index of the Cys C genes increased from 0.31 to 0.95, and the GC content was adjusted from 64.85% to 54.88%. The purity of ¹⁵N-Cys C was higher than 95%. MALDI-TOF MS analysis showed that the m/z of ¹⁵N-Cys C had changed from 13 449 to 14 850. The characteristic peptides showed that 619.79 m/z (M+2H)²⁺ was the parent ion of ¹⁵N-Cys C and that the secondary ions of ¹⁵N-labeled peptides from y⁺⁵ to y⁺⁹ were 616.27 m/z, 716.33 m/z, 788.39 m/z, 936.43 m/z, and 1052.46 m/z, respectively. In conclusion, we successfully expressed, purified and identified of ¹⁵N-Cys C protein in Escheichia coli intended for absolute quantification using ID/MS.

Gingival Crevicular Fluid Peptidome Profiling in Healthy and in Periodontal Diseases

Given its intrinsic nature, gingival crevicular fluid (GCF) is an attractive source for the discovery of novel biomarkers of periodontal diseases. GCF contains antimicrobial peptides and small proteins which could play a role in specific immune-inflammatory responses to guarantee healthy gingival status and to prevent periodontal diseases. Presently, several proteomics studies have been performed leading to increased coverage of the GCF proteome, however fewer efforts have been done to explore its natural peptides. To fill such gap, this review provides an overview of the mass spectrometric platforms and experimental designs aimed at GCF peptidome profiling, including our own data and experiences gathered from over several years of matrix-assisted laser desorption ionization/time of flight mass spectrometry (MALDI-TOF MS) based approach in this field. These tools might be useful for capturing snapshots containing diagnostic clinical information on an individual and population scale, which may be used as a specific code not only for the diagnosis of the nature or the stage of the inflammatory process in periodontal disease, but more importantly, for its prognosis, which is still an unmet medical need. As a matter of fact, current peptidomics investigations suffer from a lack of standardized procedures, posing a serious problem for data interpretation. Descriptions of the efforts to address such concerns will be highlighted.

Development of a MALDI MS-based platform for early detection of acute kidney injury

PURPOSE

Septic acute kidney injury (AKI) is associated with poor outcome. This can partly be attributed to delayed diagnosis and incomplete understanding of the underlying pathophysiology. Our aim was to develop an early predictive test for AKI based on the analysis of urinary peptide biomarkers by MALDI-MS.

EXPERIMENTAL DESIGN

Urine samples from 95 patients with sepsis were analyzed by MALDI-MS. Marker search and multimarker model establishment were performed using the peptide profiles from 17 patients with existing or within the next 5 days developing AKI and 17 with no change in renal function. Replicates of urine sample pools from the AKI and non-AKI patient groups and normal controls were also included to select the analytically most robust AKI markers.

RESULTS

Thirty-nine urinary peptides were selected by cross-validated variable selection to generate a support vector machine multidimensional AKI classifier. Prognostic performance of the AKI classifier on an independent validation set including the remaining 61 patients of the study population (17 controls and 44 cases) was good with an area under the receiver operating characteristics curve of 0.82 and a sensitivity and specificity of 86% and 76%, respectively.

CONCLUSION AND CLINICAL RELEVANCE

A urinary peptide marker model detects onset of AKI with acceptable accuracy in septic patients. Such a platform can eventually be transferred to the clinic as fast MALDI-MS test format.

State-of-the-art nanoplatform-integrated MALDI-MS impacting resolutions in urinary proteomics

Urine proteomics has become a subject of interest, since it has led to a number of breakthroughs in disease diagnostics. Urine contains information not only from the kidney and the urinary tract but also from other organs, thus urinary proteome analysis allows for identification of biomarkers for both urogenital and systemic diseases. The following review gives a brief overview of the analytical techniques that have been in practice for urinary proteomics. MALDI-MS technique and its current application status in this area of clinical research have been discussed. The review comments on the challenges facing the conventional MALDI-MS technique and the upgradation of this technique with the introduction of nanotechnology. This review projects nano-based techniques such as nano-MALDI-MS, surface-assisted laser desorption/ionization, and nanostructure-initiator MS as the platforms that have the potential in trafficking MALDI-MS from the lab to the bedside.

MALDI-TOF MS as evolving cancer diagnostic tool: a review

Recent developments in mass spectrometry have introduced clinical proteomics to the forefront of diseases diagnosis, offering reliable, robust and efficient analytical method for biomarker discovery and monitoring. MALDI-TOF is a powerful tool for surveying proteins and peptides comprising the realm for clinical analysis. MALDI-TOF has the potential to revolutionize cancer diagnostics by facilitating biomarker discovery, enabling tissue imaging and quantifying biomarker levels. Healthy (control) and cancerous tissues can be analyzed on the basis of mass spectrometry (MALDI-TOF) imaging to identify cancer-specific changes that may prove to be clinically useful. We review MALDI-TOF profiling techniques as tools for detection of cancer biomarkers in various cancers. We mainly discuss recent advances including period from 2011 to 2013.

Classical MALDI-MS versus CE-based ESI-MS proteomic profiling in urine for clinical applications

Human urine is an attractive and informative biofluid for medical diagnosis, which has been shown to reflect the (patho)-physiology of not only the urogenital system, but also others such as the cardiovascular system. For this reason, many studies have concentrated on the study of the urine proteome, aiming to find relevant biomarkers that could be applied in a clinical setting. However, this goal can only be achieved after reliable quantitative and qualitative analysis of the urinary proteome. In the last two decades, MS-based platforms have evolved to become indispensable tools for biomarker research. In this review, we will present and compare two of the most clinically relevant analytical platforms that have been used for the study of the urinary proteome, namely CE-based ESI-MS and classical MALDI-MS. These platforms, although not directly comparable, have been extensively used in proteomic profiling and therefore their comparison is fundamentally relevant to this field.

Rapid detection of antibiotic resistance based on mass spectrometry and stable isotopes

With the emergence and growing complexity of bacterial drug resistance, rapid and reliable susceptibility testing has become a topical issue. Therefore, new technologies that assist in predicting the effectiveness of empiric antibiotic therapy are of great interest. Although the use of matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) for the rapid detection of antibiotic resistance is an attractive option, the current methods for MALDI-TOF MS susceptibility testing are restricted to very limited conditions. Here, we describe a technique that may allow for rapid susceptibility testing to an extent that is comparable to phenotypic methods. The test was based on a stable isotope labelling by amino acids in cell culture (SILAC)-like approach. This technique was used to visualise the growth of bacteria in the presence of an antibiotic. Pseudomonas aeruginosa was chosen as the model organism, and strains were incubated in normal medium, medium supplemented with (13)C6-(15) N2-labelled lysine and medium supplemented with labelled lysine and antibiotic. Peak shifts occurring due to the incorporation of the labelled amino acids were detected by MALDI-TOF MS. Three antibiotics with different mechanisms of action, meropenem, tobramycin and ciprofloxacin, were tested. A semi-automated algorithm was created to enable rapid and unbiased data evaluation. With the proposed test, a clear distinction between resistant and susceptible isolates was possible for all three antibiotics. The application of SILAC technology for the detection of antibiotic resistance may contribute to accelerated and reliable susceptibility testing.