BERNN: Enhancing classification of Liquid Chromatography Mass Spectrometry data with batch effect removal neural networks

Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for profiling complex biological samples. However, batch effects typically arise from differences in sample processing protocols, experimental conditions, and data acquisition techniques, significantly impacting the interpretability of results. Correcting batch effects is crucial for the reproducibility of omics research, but current methods are not optimal for the removal of batch effects without compressing the genuine biological variation under study. We propose a suite of Batch Effect Removal Neural Networks (BERNN) to remove batch effects in large LC-MS experiments, with the goal of maximizing sample classification performance between conditions. More importantly, these models must efficiently generalize in batches not seen during training. A comparison of batch effect correction methods across five diverse datasets demonstrated that BERNN models consistently showed the strongest sample classification performance. However, the model producing the greatest classification improvements did not always perform best in terms of batch effect removal. Finally, we show that the overcorrection of batch effects resulted in the loss of some essential biological variability. These findings highlight the importance of balancing batch effect removal while preserving valuable biological diversity in large-scale LC-MS experiments

Mass Spectrometry-based Absolute Quantification of 20S Proteasome Status for Controlled Ex-vivo Expansion of Human Adipose-derived Mesenchymal Stromal/Stem Cells

International audienceIn Brief 20S proteasomes are very heterogeneous protein complexes involved in many cellular processes. In the present study, we combined an MRM-based assay with the production and purification of entire SILAC labelled pro-teasome to monitor absolute quantities of the different 20S proteasome subtypes in various human cells and tissues. This method applied to adipocyte-derived stem cells (ADSCs) amplified under various conditions highlights an increased expression of immunoproteasome when this type of cell is primed with IFN␥ or amplified in a 20% O 2 environment. Graphical Abstract Highlights • Design of an MRM assay to determine the absolute quantity and stoichiometry of ubiquitous and tissue-specific human 20S proteasome subtypes. • Use of purified isotopically labelled 20S proteasome as internal standard for accurate quantification. • Variation in the expression of immunoproteasome in adipocyte-derived stem cells (ADSCs) grown under different O 2 levels might be causal for change in cells differentiation capacity. • The status of 20S proteasome during ADSCs expansion might constitute an additional relevant quality control parameter to contribute to predict, among other quality markers, their therapeutic capacity

Activation of a PAK-MEK signalling pathway in malaria parasite-infected erythrocytes

Merozoites of malaria parasites invade red blood cells (RBCs), where they multiply by schizogony, undergoing development through ring, trophozoite and schizont stages that are responsible for malaria pathogenesis. Here, we report that a protein kinase-mediated signalling pathway involving host RBC PAK1 and MEK1, which do not have orthologues in the Plasmodium kinome, is selectively stimulated in Plasmodium falciparum-infected (versus uninfected) RBCs, as determined by the use of phospho-specific antibodies directed against the activated forms of these enzymes. Pharmacological interference with host MEK and PAK function using highly specific allosteric inhibitors in their known cellular IC50 ranges results in parasite death. Furthermore, MEK inhibitors have parasiticidal effects in vitro on hepatocyte and erythrocyte stages of the rodent malaria parasite Plasmodium berghei, indicating conservation of this subversive strategy in malaria parasites. These findings have profound implications for the development of novel strategies for antimalarial chemotherapy

Glutathione peroxidase 3 is a potential biomarker for konzo.

Konzo is a neglected paralytic neurological disease associated with food (cassava) poisoning that affects the worlds poorest children and women of childbearing ages across regions of sub-Saharan Africa. Despite understanding the dietary factors that lead to konzo, the molecular markers and mechanisms that trigger this disease remain unknown. To identify potential protein biomarkers associated with a disease status, plasma was collected from two independent Congolese cohorts, a discovery cohort (n = 60) and validation cohort (n = 204), sampled 10 years apart and subjected to multiple high-throughput assays. We identified that Glutathione Peroxidase 3 (GPx3), a critical plasma-based antioxidant enzyme, was the sole protein examined that was both significantly and differentially abundant between affected and non-affected participants in both cohorts, with large reductions observed in those affected with konzo. Our findings raise the notion that reductions in key antioxidant mechanisms may be the biological risk factor for the development of konzo, particularly those mediated through pathways involving the glutathione peroxidase family

Portrait of blood-derived extracellular vesicles in patients with Parkinson's disease.

The production of extracellular vesicles (EV) is a ubiquitous feature of eukaryotic cells but pathological events can affect their formation and constituents. We sought to characterize the nature, profile and protein signature of EV in the plasma of Parkinson's disease (PD) patients and how they correlate to clinical measures of the disease. EV were initially collected from cohorts of PD (n = 60; Controls, n = 37) and Huntington's disease (HD) patients (Pre-manifest, n = 11; manifest, n = 52; Controls, n = 55) - for comparative purposes in individuals with another chronic neurodegenerative condition - and exhaustively analyzed using flow cytometry, electron microscopy and proteomics. We then collected 42 samples from an additional independent cohort of PD patients to confirm our initial results. Through a series of iterative steps, we optimized an approach for defining the EV signature in PD. We found that the number of EV derived specifically from erythrocytes segregated with UPDRS scores corresponding to different disease stages. Proteomic analysis further revealed that there is a specific signature of proteins that could reliably differentiate control subjects from mild and moderate PD patients. Taken together, we have developed/identified an EV blood-based assay that has the potential to be used as a biomarker for PD

Mass spectrometry-based absolute quantification of 20S proteasome status for controlled ex-vivo expansion of Human Adipose-derived Mesenchymal Stromal/Stem Cells

The proteasome controls a multitude of cellular processes through protein degradation and has been identified as a therapeutic target in oncology. However, our understanding of its function and the development of specific modulators are hampered by the lack of a straightforward method to determine the overall proteasome status in biological samples. Here, we present a method to determine the absolute quantity and stoichiometry of ubiquitous and tissue-specific human 20S proteasome subtypes based on a robust, absolute SILAC-based multiplexed LC-Selected Reaction Monitoring (SRM) quantitative mass spectrometry assay with high precision, accuracy, and sensitivity. The method was initially optimized and validated by comparison with a reference ELISA assay and by analyzing the dynamics of catalytic subunits in HeLa cells following IFNγ-treatment and in range of human tissues. It was then successfully applied to reveal IFNγ- and O2-dependent variations of proteasome status during primary culture of Adipose-derived-mesenchymal Stromal/Stem Cells (ADSCs). The results show the critical importance of controlling the culture conditions during cell expansion for future therapeutic use in humans. We hypothesize that a shift from the standard proteasome to the immunoproteasome could serve as a predictor of immunosuppressive and differentiation capacities of ADSCs and, consequently, that quality control should include proteasomal quantification in addition to examining other essential cell parameters. The method presented also provides a new powerful tool to conduct more individualized protocols in cancer or inflammatory diseases where selective inhibition of the immunoproteasome has been shown to reduce side effects

High Abundance Proteins Depletion vs Low Abundance Proteins Enrichment: Comparison of Methods to Reduce the Plasma Proteome Complexity

BACKGROUND: To date, the complexity of the plasma proteome exceeds the analytical capacity of conventional approaches to isolate lower abundance proteins that may prove to be informative biomarkers. Only complex multistep separation strategies have been able to detect a substantial number of low abundance proteins (<100 ng/ml). The first step of these protocols is generally the depletion of high abundance proteins by the use of immunoaffinity columns or, alternatively, the enrichment of by the use of solid phase hexapeptides ligand libraries. METHODOLOGY/PRINCIPAL FINDINGS: Here we present a direct comparison of these two approaches. Following either approach, the plasma sample was further fractionated by SCX chromatography and analyzed by RP-LC-MS/MS with a Q-TOF mass spectrometer. The depletion of the 20 most abundant plasma proteins allowed the identification of about 25% more proteins than those detectable following low abundance proteins enrichment. The two datasets are partially overlapping and the identified proteins belong to the same order of magnitude in terms of plasma concentration. CONCLUSIONS/SIGNIFICANCE: Our results show that the two approaches give complementary results. However, the enrichment of low abundance proteins has the great advantage of obtaining much larger amount of material that can be used for further fractionations and analyses and emerges also as a cheaper and technically simpler approach. Collectively, these data indicate that the enrichment approach seems more suitable as the first stage of a complex multi-step fractionation protocol

Computational Prediction of Host-Parasite Protein Interactions between P. falciparum and H. sapiens

To obtain candidates of interactions between proteins of the malaria parasite Plasmodium falciparum and the human host, homologous and conserved interactions were inferred from various sources of interaction data. Such candidate interactions were assessed by applying a machine learning approach and further filtered according to expression and molecular characteristics, enabling involved proteins to indeed interact. The analysis of predicted interactions indicated that parasite proteins predominantly target central proteins to take control of a human host cell. Furthermore, parasite proteins utilized their protein repertoire in a combinatorial manner, providing a broad connection to host cellular processes. In particular, several prominent pathways of signaling and regulation proteins were predicted to interact with parasite chaperones. Such a result suggests an important role of remodeling proteins in the interaction interface between the human host and the parasite. Identification of such molecular strategies that allow the parasite to take control of the host has the potential to deepen our understanding of the parasite specific remodeling processes of the host cell and illuminate new avenues of disease intervention

Biomarker Analysis of Stored Blood Products: Emphasis on Pre-Analytical Issues

Millions of blood products are transfused every year; many lives are thus directly concerned by transfusion. The three main labile blood products used in transfusion are erythrocyte concentrates, platelet concentrates and fresh frozen plasma. Each of these products has to be stored according to its particular components. However, during storage, modifications or degradation of those components may occur, and are known as storage lesions. Thus, biomarker discovery of in vivo blood aging as well as in vitro labile blood products storage lesions is of high interest for the transfusion medicine community. Pre-analytical issues are of major importance in analyzing the various blood products during storage conditions as well as according to various protocols that are currently used in blood banks for their preparations. This paper will review key elements that have to be taken into account in the context of proteomic-based biomarker discovery applied to blood banking