Intact cell mass spectrometry coupled with machine learning reveals minute changes induced by single gene silencing

Intact (whole) cell MALDI TOF mass spectrometry is a commonly used tool in clinical microbiology for several decades. Recently it was introduced to analysis of eukaryotic cells, including cancer and stem cells. Besides targeted metabolomic and proteomic applications, the intact cell MALDI TOF mass spectrometry provides a sufficient sensitivity and specificity to discriminate cell types, isogenous cell lines or even the metabolic states. This makes the intact cell MALDI TOF mass spectrometry a promising tool for quality control in advanced cell cultures with a potential to reveal batch-to-batch variation, aberrant clones, or unwanted shifts in cell phenotype. However, cellular alterations induced by change in expression of a single gene has not been addressed by intact cell mass spectrometry yet. In this work we used a well-characterized human ovarian cancer cell line SKOV3 with silenced expression of a tumor suppressor candidate 3 gene (TUSC3). TUSC3 is involved in co-translational N-glycosylation of proteins with well-known global impact on cell phenotype. Altogether, this experimental design represents a highly suitable model for optimization of intact cell mass spectrometry and analysis of spectral data. Here we investigated five machine learning algorithms (k-nearest neighbors, decision tree, random forest, partial least squares discrimination, and artificial neural network) and optimized their performance either in pure populations or in two-component mixtures composed of cells with normal or silenced expression of TUSC3. All five algorithms reached accuracy over 90 % and were able to reveal even subtle changes in mass spectra corresponding to alterations of TUSC3 expression. In summary, we demonstrate that spectral fingerprints generated by intact cell MALDI-TOF mass spectrometry coupled to a machine learning classifier can reveal minute changes induced by alteration of a single gene, and therefore contribute to the portfolio of quality control applications in routine cell and tissue cultures.

Advances in high-throughput mass spectrometry in drug discovery

High-throughput (HT) screening drug discovery, during which thousands or millions of compounds are screened, remains the key methodology for identifying active chemical matter in early drug discovery pipelines. Recent technological developments in mass spectrometry (MS) and automation have revolutionized the application of MS for use in HT screens. These methods allow the targeting of unlabelled biomolecules in HT assays, thereby expanding the breadth of targets for which HT assays can be developed compared to traditional approaches. Moreover, these label-free MS assays are often cheaper, faster, and more physiologically relevant than competing assay technologies. In this review, we will describe current MS techniques used in drug discovery and explain their advantages and disadvantages. We will highlight the power of mass spectrometry in label-free in vitro assays, and its application for setting up multiplexed cellular phenotypic assays, providing an exciting new tool for screening compounds in cell lines, and even primary cells. Finally, we will give an outlook on how technological advances will increase the future use and the capabilities of mass spectrometry in drug discovery.

MALDI-TOF MS: application in diagnosis, dereplication, biomolecule profiling and microbial ecology

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has revolutionized scientific research over the past few decades and has provided a unique platform in ongoing technological developments. Undoubtedly, there has been a bloom chiefly in the field of biological sciences with this emerging technology, and has enabled researchers to generate critical data in the field of disease diagnoses, drug development, dereplication. It has received well acceptance in the field of microbial identification even at strain level, as well as diversified field like biomolecule profiling (proteomics and lipidomics) has evolved tremendously. Additionally, this approach has received a lot more attention over conventional technologies due to its high throughput, speed, and cost effectiveness. This review aims to provide a detailed insight regarding the application of MALDI-TOF MS in the context of medicine, biomolecule profiling, dereplication, and microbial ecology. In general, the expansion in the application of this technology and new advancements it has made in the field of science and technology has been highlighted.

Toward improvement of screening through mass spectrometry-based proteomics: ovarian cancer as a case study

Ovarian cancer is one of the leading causes of cancer related deaths affecting United States women. Early-stage detection of ovarian cancer has been linked to increased survival, however, current screening methods, such as biomarker testing, have proven to be ineffective in doing so. Therefore, further developments are necessary to be able to achieve positive patient prognosis. Ongoing efforts are being made in biomarker discovery towards clinical applications in screening for early-stage ovarian cancer. In this perspective, we discuss and provide examples for several workflows employing mass spectrometry-based proteomics towards protein biomarker discovery and characterization in the context of ovarian cancer; workflows include protein identification and characterization as well as intact protein profiling. We also discuss the opportunities to merge these workflows for a multiplexed approach for biomarkers. Lastly, we provide our insight as to future developments that may serve to enhance biomarker discovery workflows while also considering translational potential.

Heme Determination and Quantification Methods and Their Suitability for Practical Applications and Everyday Use

Many research institutions, clinical diagnostic laboratories, and blood banks are desperately searching for a possibility to identify and quantify heme in different physiological and pathological settings as well as various research applications. The reasons for this are the toxicity of the heme and the fact that it acts as a hemolytic and pro-inflammatory molecule. Heme only exerts these severe and undesired effects when it is not incorporated in hemoproteins. Upon release from the hemoproteins, it enters a biologically available state (labile heme), in which it is loosely associated with proteins, lipids, nucleic acids, or other molecules. While the current methods and procedures for quantitative determination of heme have been used for many years in different settings, their value is limited by the challenging chemical properties of heme. A major cause of inadequate quantification is the separation of labile and permanently bound heme and its high aggregation potential. Thus, none of the current methods are utilized as a generally applicable, standardized approach. The aim of this Feature is to describe and summarize the most common and frequently used chemical, analytical, and biochemical methods for the quantitative determination of heme. Based on this overview, the most promising approaches for future solutions to heme quantification are highlighted.

Detection of Ovarian Cancer Using Samples Sourced from the Vaginal Microenvironment

Mass spectrometry (MS) offers high levels of specificity and sensitivity in clinical applications, and we have previously been able to demonstrate that matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS is capable of distinguishing two-component cell mixtures at low limits of detection. Ovarian cancer is notoriously difficult to detect due to the lack of diagnostic techniques available to the medical community. By sampling a local microenvironment, such as the vaginal canal and cervix, a MS based method is presented for monitoring disease progression from proximal samples to the diseased tissue. A murine xenograft model of high grade serous ovarian carcinoma (HGSOC) was used for this study, and vaginal lavages were obtained from mice on a weekly basis throughout disease progression and subjected to our MALDI-TOF MS workflow followed by statistical analyses. Proteins in the 4-20 kDa region of the mass spectrum yielded a fingerprint that we could consistently measure over time that correlated with disease progression. These fingerprints were found to be largely stable across all mice, with the protein fingerprint converging toward the end point of the study. MALDI-TOF MS serves as a unique analytical technique for measuring a sampled vaginal microenvironment in a specific and sensitive manner for the detection of HGSOC in a murine model.

Intact-Cell MALDI-ToF Mass Spectrometry for the Authentication of Drug-Adapted Cancer Cell Lines

The use of cell lines in research can be affected by cell line misidentification. Short tandem repeat (STR) analysis is an effective method, and the gold standard, for the identification of the genetic origin of a cell line, but methods that allow the discrimination between cell lines of the same genetic origin are lacking. Here, we use intact cell MALDI-ToF mass spectrometry analysis, routinely used for the identification of bacteria in clinical diagnostic procedures, for the authentication of a set of cell lines consisting of three parental neuroblastoma cell lines (IMR-5, IMR-32 and UKF-NB-3) and eleven drug-adapted sublines. Principal component analysis (PCA) of intact-cell MALDI-ToF mass spectrometry data revealed clear differences between most, but not all, of the investigated cell lines. Mass spectrometry whole-cell fingerprints enabled the separation of IMR-32 and its clonal subline IMR-5. Sublines that had been adapted to closely related drugs, for example, the cisplatin- and oxaliplatin-resistant UKF-NB-3 sublines and the vincristine- and vinblastine-adapted IMR-5 sublines, also displayed clearly distinctive patterns. In conclusion, intact whole-cell MALDI-ToF mass spectrometry has the potential to be further developed into an authentication method for mammalian cells of a common genetic origin.

Mechanistic MALDI-TOF Cell-Based Assay for the Discovery of Potent and Specific Fatty Acid Synthase Inhibitors

Human cancers require fatty acid synthase (FASN)-dependent de novo long-chain fatty acid synthesis for proliferation. FASN is therefore an attractive drug target, but fast technologies for reliable label-free cellular compound profiling are lacking. Recently, MALDI-mass spectrometry (MALDI-MS) has emerged as an effective technology for discovery of recombinant protein target inhibitors. Here we present an automated, mechanistic MALDI-MS cell assay, which monitors accumulation of the FASN substrate, malonyl-coenzyme A (CoA), in whole cells with limited sample preparation. Profiling of inhibitors, including unpublished compounds, identified compound 1 as the most potent FASN inhibitor (1 nM in A549 cells) discovered to date. Moreover, cellular MALDI-MS assays enable parallel profiling of additional pathway metabolites. Surprisingly, several compounds triggered cytidine 5'-diphosphocholine (CDP-choline) but not malonyl-CoA accumulation indicating that they inhibit diacylglycerol generation but not FASN activity. Taken together, our study suggests that MALDI-MS cell assays may become important tools in drug profiling that provide additional mechanistic insights concerning compound action on metabolic pathways.

Whole Cell MALDI Fingerprinting Is a Robust Tool for Differential Profiling of Two-Component Mammalian Cell Mixtures

MALDI fingerprinting was first described two decades ago as a technique to identify microbial cell lines. Microbial fingerprinting has since evolved into an automated platform for microorganism identification and classification, which is now routinely used in clinical and environmental sectors. The extension of fingerprinting to mammalian cells has yet to progress partly due to compartmentalization of eukaryotic cells and overall higher cellular complexity. A number of publications on mammalian whole cell fingerprinting suggest that the method could be useful for classification of different cell types, cell states, and monitoring cell differentiation. We report the optimization of MALDI fingerprinting workflow parameters for mammalian cells and its application for differential profiling of mammalian cell lines and two-component cell line mixtures. Murine fallopian tube cells and high-grade ovarian carcinoma cell lines and their mixtures are used as model mammalian cell lines. Two-component cell mixtures serve to determine the method's feasibility for complex biological samples as the ability to detect cancer cells in a mixed cell population. The level of detection of cancer cells in the two-component mixture by principle component analysis (PCA) starts to deteriorate at 5% but with application of a different statistical approach, Wilcoxon rank sum test, the level of detection was determined to be 1%. The ability to differentiate heterogeneous cell mixtures will help further extend whole cell MALDI fingerprinting to complex biological systems. Graphical Abstract.

Automated analysis of lipid drug-response markers by combined fast and high-resolution whole cell MALDI mass spectrometry biotyping

Recent advances in matrix-assisted laser desorption/ionization (MALDI) mass spectrometry have enabled whole cell-MALDI mass spectrometry biotyping of drug-treated cultured cells for rapid monitoring of known abundant pharmacodynamic protein markers such as polyacetylated histones. In contrast, generic and automated analytical workflows for discovery of such pharmacodynamic markers, in particular lipid markers, and their use in cellular tests of drug-like compounds are still lacking. Here, we introduce such a workflow and demonstrate its utility for cellular drug-response monitoring of BCR-ABL tyrosine kinase inhibitors in K562 leukemia cells: First, low-molecular mass features indicating drug responses are computationally extracted from groups of MALDI-TOF mass spectra. Then, the lipids/metabolites corresponding to these features are identified by MALDI-Fourier transformation mass spectrometry. To demonstrate utility of the method, we identify the potassium adduct of phosphatidylcholine PC(36:1) as well as heme B, a marker for erythroid differentiation, as markers for a label-free MALDI MS-based test of cellular responses to BCR-ABL inhibitors. Taken together, these results suggest that MALDI-TOF mass spectrometry of lipids and other low molecular mass metabolites could support cell-based drug profiling.

Coupling MALDI-TOF mass spectrometry protein and specialized metabolite analyses to rapidly discriminate bacterial function

Mass spectrometry is a powerful technique that has been used to identify bacteria by their protein content and to assess bacterial functional traits through analysis of their specialized metabolites. However, until now these analyses have operated independently, which has resulted in the inability to rapidly connect bacterial phylogenetic identity with potential environmental function. To bridge this gap, we designed a MALDI-TOF mass spectrometry data acquisition and bioinformatics pipeline (IDBac) to integrate data from both intact protein and specialized metabolite spectra directly from bacterial cells grown on agar. This technique organizes bacteria into highly similar phylogenetic groups and allows for comparison of metabolic differences of hundreds of isolates in just a few hours.

For decades, researchers have lacked the ability to rapidly correlate microbial identity with bacterial metabolism. Since specialized metabolites are critical to bacterial function and survival in the environment, we designed a data acquisition and bioinformatics technique (IDBac) that utilizes in situ matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze protein and specialized metabolite spectra recorded from single bacterial colonies picked from agar plates. We demonstrated the power of our approach by discriminating between two Bacillus subtilis strains in <30 min solely on the basis of their differential ability to produce cyclic peptide antibiotics surfactin and plipastatin, caused by a single frameshift mutation. Next, we used IDBac to detect subtle intraspecies differences in the production of metal scavenging acyl-desferrioxamines in a group of eight freshwater Micromonospora isolates that share >99% sequence similarity in the 16S rRNA gene. Finally, we used IDBac to simultaneously extract protein and specialized metabolite MS profiles from unidentified Lake Michigan sponge-associated bacteria isolated from an agar plate. In just 3 h, we created hierarchical protein MS groupings of 11 environmental isolates (10 MS replicates each, for a total of 110 spectra) that accurately mirrored phylogenetic groupings. We further distinguished isolates within these groupings, which share nearly identical 16S rRNA gene sequence identity, based on interspecies and intraspecies differences in specialized metabolite production. IDBac is an attempt to couple in situ MS analyses of protein content and specialized metabolite production to allow for facile discrimination of closely related bacterial colonies.

In Situ Characterization of Tissue-Resident Immune Cells by MALDI Mass Spectrometry Imaging

Tissue-resident immune cells differ from their corresponding blood cells in many functional aspects. Although the proteome of blood immune cells has been well-investigated, there are almost no data on tissue-resident immune cells. Here, we explored the potential of using MALDI-TOF-MS imaging (MSI) to investigate these cells in colon tissue, which exhibits a strong infiltration of immune cells. MSI identified several proteinaceous markers that colocalized with specific structures of the colon, such as mucosa or muscularis mucosae, in six patients. In addition, we showed that certain m/z values have the same spatial distribution as CD3⁺ T lymphocytes in the lymphoid follicular structures or as CD206⁺ macrophages in the lamina propria. For further corroboration, blood lymphocytes and monocytes from 10 healthy volunteers were analyzed by intact cell mass spectrometry (ICMS). Furthermore, we analyzed monocyte-derived macrophages that had been polarized in vitro into proinflammatory M₁ and anti-inflammatory M₂ phenotypes. The mass spectra differed clearly among all immune cell types. Additionally, it was found that distinct signals from ICMS analysis were identical to the m/z values found in the MSI experiment in lymphoid follicular structures. These data show for the first time that MSI is well-suited to visualize the spatial distribution of immune cells in human colon tissue. We consider MALDI mass spectrometry imaging to be a technique with high potential for use in rapid investigations of tissue-specific features of cells.

Current developments to use linear MALDI-TOF spectra for the identification and typing of bacteria and the characterization of other cells/organisms related to infectious diseases

Within the past few years identification of bacteria by MALDI-TOF MS has become a standard technique in bacteriological laboratories for good reasons. MALDI-TOF MS identification is rapid, robust, automatable, and the per-sample costs are low. Yet, the spectra are very informative and the reliable identification of bacterial species is usually possible. Recently, new MS-based approaches for the identification of bacteria are emerging that are based on the detailed analysis of the bacterial proteome by high-resolution MS. These "proteotyping" approaches are highly discriminative and outperform MALDI-TOF MS-based identification in terms of specificity, but require a laborious proteomic workflow and far more expertise and sophisticated instrumentation than identification on basis of MALDI-TOF MS spectra, which can be obtained with relative simple and uncostly linear MALDI-TOF mass spectrometers. Thus MALDI-TOF MS identification of bacteria remains an attractive option for routine diagnostics. Additionally, MALDI-TOF MS identification protocols have been extended and improved in many respects making linear MALDI-TOF MS a versatile tool that can be useful beyond the identification of a bacterial species, e.g. for the characterization of leucocytes and arthropod vectors of infectious diseases. This review focuses on such improvements and extensions of the typical MALDI-TOF MS workflow in the field of infectious diseases.

Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks

Cross-contamination of eukaryotic cell lines used in biomedical research represents a highly relevant problem. Analysis of repetitive DNA sequences, such as Short Tandem Repeats (STR), or Simple Sequence Repeats (SSR), is a widely accepted, simple, and commercially available technique to authenticate cell lines. However, it provides only qualitative information that depends on the extent of reference databases for interpretation. In this work, we developed and validated a rapid and routinely applicable method for evaluation of cell culture cross-contamination levels based on mass spectrometric fingerprints of intact mammalian cells coupled with artificial neural networks (ANNs). We used human embryonic stem cells (hESCs) contaminated by either mouse embryonic stem cells (mESCs) or mouse embryonic fibroblasts (MEFs) as a model. We determined the contamination level using a mass spectra database of known calibration mixtures that served as training input for an ANN. The ANN was then capable of correct quantification of the level of contamination of hESCs by mESCs or MEFs. We demonstrate that MS analysis, when linked to proper mathematical instruments, is a tangible tool for unraveling and quantifying heterogeneity in cell cultures. The analysis is applicable in routine scenarios for cell authentication and/or cell phenotyping in general.

In search of the molecular mechanisms mediating the inhibitory effect of the GnRH antagonist degarelix on human prostate cell growth

Degarelix is a gonadrotropin-releasing hormone (GnRH) receptor (GnRHR) antagonist used in patients with prostate cancer who need androgen deprivation therapy. GnRHRs have been found in extra-pituitary tissues, including prostate, which may be affected by the GnRH and GnRH analogues used in therapy. The direct effect of degarelix on human prostate cell growth was evaluated. Normal prostate myofibroblast WPMY-1 and epithelial WPE1-NA22 cells, benign prostatic hyperplasia (BPH)-1 cells, androgen-independent PC-3 and androgen-dependent LNCaP prostate cancer cells, as well as VCaP cells derived from a patient with castration-resistant prostate cancer were used. Discriminatory protein and lipid fingerprints of normal, hyperplastic, and cancer cells were generated by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS). The investigated cell lines express GNRHR1 and GNRHR2 and their endogenous ligands. Degarelix treatment reduced cell viability in all prostate cell lines tested, with the exception of the PC-3 cells; this can be attributed to increased apoptosis, as indicated by increased caspase 3/7, 8 and 9 levels. WPE1-NA22, BPH-1, LNCaP, and VCaP cell viability was not affected by treatment with the GnRH agonists leuprolide and goserelin. Using MALDI MS, we detected changes in m/z signals that were robust enough to create a complete discriminatory profile induced by degarelix. Transcriptomic analysis of BPH-1 cells provided a global map of genes affected by degarelix and indicated that the biological processes affected were related to cell growth, G-coupled receptors, the mitogen-activated protein kinase (MAPK) pathway, angiogenesis and cell adhesion. Taken together, these data demonstrate that (i) the GnRH antagonist degarelix exerts a direct effect on prostate cell growth through apoptosis; (ii) MALDI MS analysis provided a basis to fingerprint degarelix-treated prostate cells; and (iii) the clusters of genes affected by degarelix suggest that this compound, in addition to its known use in the treatment of prostate cancer, may be efficacious in BPH.

Rapid high-throughput characterisation, classification and selection of recombinant mammalian cell line phenotypes using intact cell MALDI-ToF mass spectrometry fingerprinting and PLS-DA modelling

Despite many advances in the generation of high producing recombinant mammalian cell lines over the last few decades, cell line selection and development is often slowed by the inability to predict a cell line's phenotypic characteristics (e.g. growth or recombinant protein productivity) at larger scale (large volume bioreactors) using data from early cell line construction at small culture scale. Here we describe the development of an intact cell MALDI-ToF mass spectrometry fingerprinting method for mammalian cells early in the cell line construction process whereby the resulting mass spectrometry data are used to predict the phenotype of mammalian cell lines at larger culture scale using a Partial Least Squares Discriminant Analysis (PLS-DA) model. Using MALDI-ToF mass spectrometry, a library of mass spectrometry fingerprints was generated for individual cell lines at the 96 deep well plate stage of cell line development. The growth and productivity of these cell lines were evaluated in a 10L bioreactor model of Lonza's large-scale (up to 20,000L) fed-batch cell culture processes. Using the mass spectrometry information at the 96 deep well plate stage and phenotype information at the 10L bioreactor scale a PLS-DA model was developed to predict the productivity of unknown cell lines at the 10L scale based upon their MALDI-ToF fingerprint at the 96 deep well plate scale. This approach provides the basis for the very early prediction of cell lines' performance in cGMP manufacturing-scale bioreactors and the foundation for methods and models for predicting other mammalian cell phenotypes from rapid, intact-cell mass spectrometry based measurements.