A sensitive and simple targeted proteomics approach to quantify transcription factor and membrane proteins of the unfolded protein response pathway in glioblastoma cells

A hierarchical structure in the N-glycosylation process governs the N-glycosylation output: prolonged cultivation induces glycoenzymes expression variations that are reflected in the cellular N-glycome but not in the protein and site-specific glycoprofile of CHO cells

N-glycosylation is a central component in the modification of secretory proteins. One characteristic of this process is a heterogeneous output. The heterogeneity is the result of both structural constraints of the glycoprotein as well as the composition of the cellular glycosylation machinery. Empirical data addressing correlations between glycosylation output and glycosylation machinery composition are seldom due to the low abundance of glycoenzymes. We assessed how differences in the glycoenzyme expression affected the N-glycosylation output at a cellular as well as at a protein-specific level. Our results showed that cellular N-glycome changes could be correlated with the variation of glycoenzyme expression, whereas at the protein level differential responses to glycoenzymes alterations were observed. We therefore identified a hierarchical structure in the N-glycosylation process: the enzyme levels in this complex pathway determine its capacity (reflected in the N-glycome), while protein-specific parameters determine the glycosite-specificity. What emerges is a highly variable and adaptable protein modification system that represents a hallmark of eukaryotic cells.

Phosphoproteomics implicates glutamatergic and dopaminergic signalling in the antidepressant-like properties of the iron chelator deferiprone

BACKGROUND

Current antidepressants have limitations due to insufficient efficacy and delay before improvement in symptoms. Polymorphisms of the serotonin transporter (5-HTT) gene have been linked to depression (when combined with stressful life events) and altered response to selective serotonergic reuptake inhibitors. We have previously revealed the antidepressant-like properties of the iron chelator deferiprone in the 5-HTT knock-out (KO) mouse model of depression. Furthermore, deferiprone was found to alter neural activity in the prefrontal cortex of both wild-type (WT) and 5-HTT KO mice.

METHODS

In the current study, we examined the molecular effects of acute deferiprone treatment in the prefrontal cortex of both genotypes via phosphoproteomics analysis.

RESULTS

In WT mice treated with deferiprone, there were 22 differentially expressed phosphosites, with gene ontology analysis implicating cytoskeletal proteins. In 5-HTT KO mice treated with deferiprone, we found 33 differentially expressed phosphosites. Gene ontology analyses revealed phosphoproteins that were predominantly involved in synaptic and glutamatergic signalling. In a drug-naïve cohort (without deferiprone administration), the analysis revealed 21 differentially expressed phosphosites in 5-HTT KO compared to WT mice. We confirmed the deferiprone-induced increase in tyrosine hydroxylase serine 40 residue phosphorylation (pTH-Ser40) (initially revealed in our phosphoproteomics study) by Western blot analysis, with deferiprone increasing pTH-Ser40 expression in WT and 5-HTT KO mice.

CONCLUSION

As glutamatergic and synaptic signalling are dysfunctional in 5-HTT KO mice (and are the target of fast-acting antidepressant drugs such as ketamine), these molecular effects may underpin deferiprone's antidepressant-like properties. Furthermore, dopaminergic signalling may also be involved in deferiprone's antidepressant-like properties.

Proteomics Applications in Toxoplasma gondii: Unveiling the Host-Parasite Interactions and Therapeutic Target Discovery

Toxoplasma gondii, a protozoan parasite with the ability to infect various warm-blooded vertebrates, including humans, is the causative agent of toxoplasmosis. This infection poses significant risks, leading to severe complications in immunocompromised individuals and potentially affecting the fetus through congenital transmission. A comprehensive understanding of the intricate molecular interactions between T. gondii and its host is pivotal for the development of effective therapeutic strategies. This review emphasizes the crucial role of proteomics in T. gondii research, with a specific focus on host-parasite interactions, post-translational modifications (PTMs), PTM crosstalk, and ongoing efforts in drug discovery. Additionally, we provide an overview of recent advancements in proteomics techniques, encompassing interactome sample preparation methods such as BioID (BirA*-mediated proximity-dependent biotin identification), APEX (ascorbate peroxidase-mediated proximity labeling), and Y2H (yeast two hybrid), as well as various proteomics approaches, including single-cell analysis, DIA (data-independent acquisition), targeted, top-down, and plasma proteomics. Furthermore, we discuss bioinformatics and the integration of proteomics with other omics technologies, highlighting its potential in unraveling the intricate mechanisms of T. gondii pathogenesis and identifying novel therapeutic targets.

Targeted Proteomic Quantitation of NRF2 Signaling and Predictive Biomarkers in HNSCC

The NFE2L2 (NRF2) oncogene and transcription factor drives a gene expression program that promotes cancer progression, metabolic reprogramming, immune evasion, and chemoradiation resistance. Patient stratification by NRF2 activity may guide treatment decisions to improve outcome. Here, we developed a mass spectrometry-based targeted proteomics assay based on internal standard-triggered parallel reaction monitoring to quantify 69 NRF2 pathway components and targets, as well as 21 proteins of broad clinical significance in head and neck squamous cell carcinoma (HNSCC). We improved an existing internal standard-triggered parallel reaction monitoring acquisition algorithm, called SureQuant, to increase throughput, sensitivity, and precision. Testing the optimized platform on 27 lung and upper aerodigestive cancer cell models revealed 35 NRF2 responsive proteins. In formalin-fixed paraffin-embedded HNSCCs, NRF2 signaling intensity positively correlated with NRF2-activating mutations and with SOX2 protein expression. Protein markers of T-cell infiltration correlated positively with one another and with human papilloma virus infection status. CDKN2A (p16) protein expression positively correlated with the human papilloma virus oncogenic E7 protein and confirmed the presence of translationally active virus. This work establishes a clinically actionable HNSCC protein biomarker assay capable of quantifying over 600 peptides from frozen or formalin-fixed paraffin-embedded archived tissues in under 90 min.

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

Recent advances in the detection of glioblastoma, from imaging-based methods to proteomics and biosensors: A narrative review

Glioblastoma (GBM) is an aggressive type of cancer that originates in the cells called astrocytes, which support the functioning of nerve cells. It can develop in either the brain or the spinal cord and is also known as glioblastoma multiform. GBM is a highly aggressive cancer that can occur in either the brain or spinal cord. The detection of GBM in biofluids offers potential advantages over current methods for diagnosing and treatment monitoring of glial tumors. Biofluid-based detection of GBM focuses on identifying tumor-specific biomarkers in blood and cerebrospinal fluid. To date, different methods have been used to detect biomarkers of GBM, ranging from various imaging techniques to molecular approaches. Each method has its own strengths and weaknesses. The present review aims to scrutinize multiple diagnostic methods for GBM, with a focus on proteomics methods and biosensors. In other words, this study aims to provide an overview of the most significant research findings based on proteomics and biosensors for the diagnosis of GBM.

Cerebrospinal fluid biomarkers for assessing Huntington disease onset and severity

The identification of molecular biomarkers in CSF from individuals affected by Huntington disease may help improve predictions of disease onset, better define disease progression and could facilitate the evaluation of potential therapies. The primary objective of our study was to investigate novel CSF protein candidates and replicate previously reported protein biomarker changes in CSF from Huntington disease mutation carriers and healthy controls. Our secondary objective was to compare the discriminatory potential of individual protein analytes and combinations of CSF protein markers for stratifying individuals based on the severity of Huntington disease. We conducted a hypothesis-driven analysis of 26 pre-specified protein analytes in CSF from 16 manifest Huntington disease subjects, eight premanifest Huntington disease mutation carriers and eight healthy control individuals using parallel-reaction monitoring mass spectrometry. In addition to reproducing reported changes in previously investigated CSF biomarkers (NEFL, PDYN, and PENK), we also identified novel exploratory CSF proteins (C1QB, CNR1, GNAL, IDO1, IGF2, and PPP1R1B) whose levels were altered in Huntington disease mutation carriers and/or across stages of disease. Moreover, we report strong associations of select CSF proteins with clinical measures of disease severity in manifest Huntington disease subjects (C1QB, CNR1, NEFL, PDYN, PPP1R1B, and TTR) and with years to predicted disease onset in premanifest Huntington disease mutation carriers (ALB, C4B, CTSD, IGHG1, and TTR). Using receiver operating characteristic curve analysis, we identified PENK as being the most discriminant CSF protein for stratifying Huntington disease mutation carriers from controls. We also identified exploratory multi-marker CSF protein panels that improved discrimination of premanifest Huntington disease mutation carriers from controls (PENK, ALB and NEFL), early/mid-stage Huntington disease from premanifest mutation carriers (PPP1R1B, TTR, CHI3L1, and CTSD), and late-stage from early/mid-stage Huntington disease (CNR1, PPP1R1B, BDNF, APOE, and IGHG1) compared with individual CSF proteins. In this study, we demonstrate that combinations of CSF proteins can outperform individual markers for stratifying individuals based on Huntington disease mutation status and disease severity. Moreover, we define exploratory multi-marker CSF protein panels that, if validated, may be used to improve the accuracy of disease-onset predictions, complement existing clinical and imaging biomarkers for monitoring the severity of Huntington disease, and potentially for assessing therapeutic response in clinical trials. Additional studies with CSF collected from larger cohorts of Huntington disease mutation carriers are needed to replicate these exploratory findings.

The addition of FAIMS increases targeted proteomics sensitivity from FFPE tumor biopsies

Mass spectrometry-based targeted proteomics allows objective protein quantitation of clinical biomarkers from a single section of formalin-fixed, paraffin-embedded (FFPE) tumor tissue biopsies. We combined high-field asymmetric waveform ion mobility spectrometry (FAIMS) and parallel reaction monitoring (PRM) to increase assay sensitivity. The modular nature of the FAIMS source allowed direct comparison of the performance of FAIMS-PRM to PRM. Limits of quantitation were determined by spiking synthetic peptides into a human spleen matrix. In addition, 20 clinical samples were analyzed using FAIMS-PRM and the quantitation of HER2 was compared with that obtained with the Ventana immunohistochemistry assay. FAIMS-PRM improved the overall signal-to-noise ratio over that from PRM and increased assay sensitivity in FFPE tissue analysis for four (HER2, EGFR, cMET, and KRAS) of five proteins of clinical interest. FAIMS-PRM enabled sensitive quantitation of basal HER2 expression in breast cancer samples classified as HER2 negative by immunohistochemistry. Furthermore, we determined the degree of FAIMS-dependent background reduction and showed that this correlated with an improved lower limit of quantitation with FAIMS. FAIMS-PRM is anticipated to benefit clinical trials in which multiple biomarker questions must be addressed and the availability of tumor biopsy samples is limited.

Transcription factor-driven coordination of cell cycle exit and lineage-specification in vivo during granulocytic differentiation : In memoriam Professor Niels Borregaard

Differentiation of multipotent stem cells into mature cells is fundamental for development and homeostasis of mammalian tissues, and requires the coordinated induction of lineage-specific transcriptional programs and cell cycle withdrawal. To understand the underlying regulatory mechanisms of this fundamental process, we investigated how the tissue-specific transcription factors, CEBPA and CEBPE, coordinate cell cycle exit and lineage-specification in vivo during granulocytic differentiation. We demonstrate that CEBPA promotes lineage-specification by launching an enhancer-primed differentiation program and direct activation of CEBPE expression. Subsequently, CEBPE confers promoter-driven cell cycle exit by sequential repression of MYC target gene expression at the G1/S transition and E2F-meditated G2/M gene expression, as well as by the up-regulation of Cdk1/2/4 inhibitors. Following cell cycle exit, CEBPE unleashes the CEBPA-primed differentiation program to generate mature granulocytes. These findings highlight how tissue-specific transcription factors coordinate cell cycle exit with differentiation through the use of distinct gene regulatory elements.

ERK1/2 Activity Is Critical for the Outcome of Ischemic Stroke

Ischemic disorders are the leading cause of death worldwide. The extracellular signal-regulated kinases 1 and 2 (ERK1/2) are thought to affect the outcome of ischemic stroke. However, it is under debate whether activation or inhibition of ERK1/2 is beneficial. In this study, we report that the ubiquitous overexpression of wild-type ERK2 in mice (ERK2^wt) is detrimental after transient occlusion of the middle cerebral artery (tMCAO), as it led to a massive increase in infarct volume and neurological deficits by increasing blood–brain barrier (BBB) leakiness, inflammation, and the number of apoptotic neurons. To compare ERK1/2 activation and inhibition side-by-side, we also used mice with ubiquitous overexpression of the Raf-kinase inhibitor protein (RKIP^wt) and its phosphorylation-deficient mutant RKIP^S153A, known inhibitors of the ERK1/2 signaling cascade. RKIP^wt and RKIP^S153A attenuated ischemia-induced damages, in particular via anti-inflammatory signaling. Taken together, our data suggest that stimulation of the Raf/MEK/ERK1/2-cascade is severely detrimental and its inhibition is rather protective. Thus, a tight control of the ERK1/2 signaling is essential for the outcome in response to ischemic stroke.

Analytical comparison of absolute quantification strategies to investigate the Insulin signaling pathway in fat cells

So far, mass spectrometry based targeted proteomics is the most sensitive approach to answer and address specific biological questions in an accurate and quantitative fashion. However, the data analysis design used for such quantification varies in the field leading to discrepancies in the reported values. In this study, different quantification strategies based on calibration curves were evaluated and compared. The best accuracy and coefficient of variation was achieved by ratio to ratio calibration curves. We applied the ratio to ratio quantification approach to analyze very low abundant insulin signaling proteins such as PIK3RA (0.10-0.93 fmol/μg), AKT1 (0.1-0.39 fmol/μg) and the Insulin receptor (0.22 -2.62 fmol/μg) in a fat cell model and demonstrated the adaptation of this pathway at different states of insulin sensitivity. This article is protected by copyright. All rights reserved.

RNA-Binding Protein Expression Alters Upon Differentiation of Human B Cells and T Cells

B cells and T cells are key players in the defence against infections and malignancies. To exert their function, B cells and T cells differentiate into effector and memory cells. Tight regulation of these differentiation processes is key to prevent their malfunction, which can result in life-threatening disease. Lymphocyte differentiation relies on the appropriate timing and dosage of regulatory molecules, and post-transcriptional gene regulation (PTR) is a key player herein. PTR includes the regulation through RNA-binding proteins (RBPs), which control the fate of RNA and its translation into proteins. To date, a comprehensive overview of the RBP expression throughout lymphocyte differentiation is lacking. Using transcriptome and proteome analyses, we here catalogued the RBP expression for human B cells and T cells. We observed that even though the overall RBP expression is conserved, the relative RBP expression is distinct between B cells and T cells. Differentiation into effector and memory cells alters the RBP expression, resulting into preferential expression of different classes of RBPs. For instance, whereas naive T cells express high levels of translation-regulating RBPs, effector T cells preferentially express RBPs that modulate mRNA stability. Lastly, we found that cytotoxic CD8+ and CD4+ T cells express a common RBP repertoire. Combined, our study reveals a cell type-specific and differentiation-dependent RBP expression landscape in human lymphocytes, which will help unravel the role of RBPs in lymphocyte function.

An Introduction to Advanced Targeted Acquisition Methods

Targeted proteomics via selected reaction monitoring (SRM) or parallel reaction monitoring (PRM) enables fast and sensitive detection of a preselected set of target peptides. However, the number of peptides that can be monitored in conventional targeting methods is usually rather small. Recently, a series of methods has been described that employ intelligent acquisition strategies to increase the efficiency of mass spectrometers to detect target peptides. These methods are based on one of two strategies. First, retention time adjustment-based methods enable intelligent scheduling of target peptide retention times. These include Picky, iRT, as well as spike-in free real-time adjustment methods such as MaxQuant.Live. Second, in spike-in triggered acquisition methods such as SureQuant, Pseudo-PRM, TOMAHAQ, and Scout-MRM, targeted scans are initiated by abundant labeled synthetic peptides added to samples before the run. Both strategies enable the mass spectrometer to better focus data acquisition time on target peptides. This either enables more sensitive detection or a higher number of targets per run. Here, we provide an overview of available advanced targeting methods and highlight their intrinsic strengths and weaknesses and compatibility with specific experimental setups. Our goal is to provide a basic introduction to advanced targeting methods for people starting to work in this field.

Intracellular Lipid Accumulation and Mitochondrial Dysfunction Accompanies Endoplasmic Reticulum Stress Caused by Loss of the Co-chaperone DNAJC3

Recessive mutations in DNAJC3, an endoplasmic reticulum (ER)-resident BiP co-chaperone, have been identified in patients with multisystemic neurodegeneration and diabetes mellitus. To further unravel these pathomechanisms, we employed a non-biased proteomic approach and identified dysregulation of several key cellular pathways, suggesting a pathophysiological interplay of perturbed lipid metabolism, mitochondrial bioenergetics, ER-Golgi function, and amyloid-beta processing. Further functional investigations in fibroblasts of patients with DNAJC3 mutations detected cellular accumulation of lipids and an increased sensitivity to cholesterol stress, which led to activation of the unfolded protein response (UPR), alterations of the ER-Golgi machinery, and a defect of amyloid precursor protein. In line with the results of previous studies, we describe here alterations in mitochondrial morphology and function, as a major contributor to the DNAJC3 pathophysiology. Hence, we propose that the loss of DNAJC3 affects lipid/cholesterol homeostasis, leading to UPR activation, β-amyloid accumulation, and impairment of mitochondrial oxidative phosphorylation.

Discovery of a small protein-encoding cis-regulatory overlapping gene of the tumor suppressor gene Scribble in humans

Intensive gene annotation has revealed many functional and regulatory elements in the human genome. Although eukaryotic protein-coding genes are generally transcribed into monocistronic mRNAs, recent studies have discovered additional short open reading frames (sORFs) in mRNAs. Here, we performed proteogenomic data mining for hidden proteins categorized into sORF-encoded polypeptides (SEPs) in human cancers. We identified a new SEP-encoding overlapping sORF (oORF) on the cell polarity determinant Scribble (SCRIB) that is considered a proto-oncogene with tumor suppressor function in Hippo-YAP/TAZ, MAPK/ERK, and PI3K/Akt/mTOR signaling. Reanalysis of clinical human proteomic data revealed translational dysregulation of both SCRIB and its oORF, oSCRIB, during carcinogenesis. Biochemical analyses suggested that the translatable oSCRIB constitutively limits the capacity of eukaryotic ribosomes to translate the downstream SCRIB. These findings provide a new example of cis-regulatory oORFs that function as a ribosomal roadblock and potentially serve as a fail-safe mechanism to normal cells for non-excessive downstream gene expression, which is hijacked in cancer.

Yuhta Nomura and Naoshi Dohmae report the discovery of a small protein-coding gene that overlaps the tumor suppressor gene Scribble. Their data suggest that the overlapping gene, oSCRIB, limits the translation of downstream Scribble and may have important implications in cancer.

Nano-liquid chromatography-mass spectrometry and recent applications in omics investigations

Liquid chromatography coupled to mass spectrometry (LC-MS) is one of the most powerful tools in identifying and quantitating molecular species. Decreasing column diameter from the millimeter to micrometer scale is now a well-developed method which allows for sample limited analysis. Specific fabrication of capillary columns is required for proper implementation and optimization when working in the nanoflow regime. Coupling the capillary column to the mass spectrometer for electrospray ionization (ESI) requires reduction of the subsequent emitter tip. Reduction of column diameter to capillary scale can produce improved chromatographic efficiency and the reduction of emitter tip size increased sensitivity of the electrospray process. This improved sensitivity and ionization efficiency is valuable in analysis of precious biological samples where analytes vary in size, ion affinity, and concentration. In this review we will discuss common approaches and challenges in implementing nLC-MS methods and how the advantages can be leveraged to investigate a wide range of biomolecules.

A multi-omics analysis reveals the unfolded protein response regulon and stress-induced resistance to folate-based antimetabolites

Stress response pathways are critical for cellular homeostasis, promoting survival through adaptive changes in gene expression and metabolism. They play key roles in numerous diseases and are implicated in cancer progression and chemoresistance. However, the underlying mechanisms are only poorly understood. We have employed a multi-omics approach to monitor changes to gene expression after induction of a stress response pathway, the unfolded protein response (UPR), probing in parallel the transcriptome, the proteome, and changes to translation. Stringent filtering reveals the induction of 267 genes, many of which have not previously been implicated in stress response pathways. We experimentally demonstrate that UPR‐mediated translational control induces the expression of enzymes involved in a pathway that diverts intermediate metabolites from glycolysis to fuel mitochondrial one‐carbon metabolism. Concomitantly, the cells become resistant to the folate-based antimetabolites Methotrexate and Pemetrexed, establishing a direct link between UPR‐driven changes to gene expression and resistance to pharmacological treatment.

The unfolded protein response (UPR) is a stress response pathway implicated in numerous diseases and chemotherapy resistance. Here, the authors define the UPR regulon with a multi-omics strategy, uncovering changes to mitochondrial one-carbon metabolism and concomitant resistance to folate-based therapeutics.

Quantitative Analysis of Antibody Survival across the Infant Digestive Tract Using Mass Spectrometry with Parallel Reaction Monitoring

Orally delivered antibodies may be useful for the prevention of enteric pathogen infection, but to be effective they need to survive intact across digestion through the gastrointestinal tract. As a test case, we fed a recombinant human antibody, palivizumab, spiked into human milk to four infants and collected gastric, intestinal and stool samples. We identified a tryptic peptide from palivizumab (LLIYDTSK) that differs from all endogenous human antibodies and used this for quantitation of the intact palivizumab. To account for dilution by digestive fluids, we co-fed a non-digestible, non-absorbable molecule-polyethylene glycol 28-quantified it in each sample and used this value to normalize the observed palivizumab concentration. The palivizumab peptide, a stable isotope-labeled synthetic peptide and polyethylene glycol 28 were quantified via a highly sensitive and selective parallel-reaction monitoring approach using nano-liquid chromatography/Orbitrap mass spectrometry. On average, the survival of intact palivizumab from the feed to the stomach, upper small intestine and stool were 88.4%, 30.0% and 5.2%, respectively. This approach allowed clear determination of the extent to which palivizumab was degraded within the infant digestive tract. This method can be applied with some modifications to study the digestion of any protein.

Targeted Approach to Distinguish and Determine Absolute Levels of GDF8 and GDF11 in Mouse Serum

Growth differentiation factor 11 (GDF11) is a TGF-β superfamily circulating factor that regulates cardiomyocyte size in rodents, sharing 90% amino acid sequence identity in the active domains with myostatin (GDF8)-the major determinant of skeletal muscle mass. Conflicting data on age-related changes in circulating levels have been reported mainly due to the lack of specific detection methods. More recently, liquid chromatography tandem mass spectrometry (LC-MS/MS) based assay showed that the circulating levels of GDF11 do not change significantly throughout human lifespan, but GDF8 levels decrease with aging in men. Here a novel detection method is demonstrated based on parallel reaction monitoring LC-MS/MS assay combined with immunoprecipitation to reliably distinguish GDF11 and GDF8 as well as determine their endogenous levels in mouse serum. The data indicate that both GDF11 and GDF8 circulating levels significantly decline with aging in female mice.

Sugar Beet (Beta vulgaris) Guard Cells Responses to Salinity Stress: A Proteomic Analysis

Soil salinity is a major environmental constraint affecting crop growth and threatening global food security. Plants adapt to salinity by optimizing the performance of stomata. Stomata are formed by two guard cells (GCs) that are morphologically and functionally distinct from the other leaf cells. These microscopic sphincters inserted into the wax-covered epidermis of the shoot balance CO₂ intake for photosynthetic carbon gain and concomitant water loss. In order to better understand the molecular mechanisms underlying stomatal function under saline conditions, we used proteomics approach to study isolated GCs from the salt-tolerant sugar beet species. Of the 2088 proteins identified in sugar beet GCs, 82 were differentially regulated by salt treatment. According to bioinformatics analysis (GO enrichment analysis and protein classification), these proteins were involved in lipid metabolism, cell wall modification, ATP biosynthesis, and signaling. Among the significant differentially abundant proteins, several proteins classified as "stress proteins" were upregulated, including non-specific lipid transfer protein, chaperone proteins, heat shock proteins, inorganic pyrophosphatase 2, responsible for energized vacuole membrane for ion transportation. Moreover, several antioxidant enzymes (peroxide, superoxidase dismutase) were highly upregulated. Furthermore, cell wall proteins detected in GCs provided some evidence that GC walls were more flexible in response to salt stress. Proteins such as L-ascorbate oxidase that were constitutively high under both control and high salinity conditions may contribute to the ability of sugar beet GCs to adapt to salinity by mitigating salinity-induced oxidative stress.

Developing a Robust Assay to Monitor and Quantify Key Players of Metabolic Pathways during Adipogenesis by Targeted Proteomics

Targeted data acquisition using nano liquid chromatrography (nano-LC) coupled mass spectrometry is an emerging approach when there is a need to quantify proteins with high accuracy, sensitivity, and reproducibility. Nevertheless, creating assays meeting all those criteria still remains a laborious task, especially when investigating low abundant proteins and small concentration changes. In this work a targeted data acquisition workflow is developed reducing time and effort to target and investigate key players of metabolic pathways during the process of adipocyte differentiation. This leads to accurate and sensitive quantification of proteins involved in the synthesis of fatty acids, glycerolipids, glycerophospholipids, sphingolipids, the production of energy and reduction equivalents. Additionally low abundant signaling molecules part of the peroxisome proliferator-activated receptor gamma (PPARγ) and insulin signaling pathway with ≈400 for the insulin receptor substrate and 1100 copies per cell for PPARγ are determined.

Transient hysteresis and inherent stochasticity in gene regulatory networks

Cell fate determination, the process through which cells commit to differentiated states is commonly mediated by gene regulatory motifs with mutually exclusive expression states. The classical deterministic picture for cell fate determination includes bistability and hysteresis, which enables the persistence of the acquired cellular state after withdrawal of the stimulus, ensuring a robust cellular response. However, stochasticity inherent to gene expression dynamics is not compatible with hysteresis, since the stationary solution of the governing Chemical Master Equation does not depend on the initial conditions. We provide a quantitative description of a transient hysteresis phenomenon reconciling experimental evidence of hysteretic behaviour in gene regulatory networks with inherent stochasticity: under sufficiently slow dynamics hysteresis is transient. We quantify this with an estimate of the convergence rate to the equilibrium and introduce a natural landscape capturing system’s evolution that, unlike traditional cell fate potential landscapes, is compatible with coexistence at the microscopic level.

Cell fate commitment is understood in terms of bistable regulatory circuits with hysteresis, but inherent stochasticity in gene expression is incompatible with hysteresis. Here, the authors quantify how, under slow dynamics, the dependency of the non-stationary solutions on the initial state of the cells can lead to transient hysteresis.