The redox-based modifications of cysteine residues in proteins regulate their function in many biological processes. The gas molecule H₂S has been shown to persulfidate redox sensitive cysteine residues resulting in an H₂S-modified proteome known as the sulfhydrome. Tandem Mass Tags (TMT) multiplexing strategies for large-scale proteomic analyses have become increasingly prevalent in detecting cysteine modifications. Here we developed a TMT-based proteomics approach for selectively trapping and tagging cysteine persulfides in the cellular proteomes. We revealed the natural protein sulfhydrome of two human cell lines, and identified insulin as a novel substrate in pancreatic beta cells. Moreover, we showed that under oxidative stress conditions, increased H₂S can target enzymes involved in energy metabolism by switching specific cysteine modifications to persulfides. Specifically, we discovered a Redox Thiol Switch, from protein S-glutathioinylation to S-persulfidation (RTS^GS). We propose that the RTS^GS from S-glutathioinylation to S-persulfidation is a potential mechanism to fine tune cellular energy metabolism in response to different levels of oxidative stress.

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100x) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ~2500 proteins and precise quantification of ~1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

HNF4α is a nuclear receptor produced as 12 isoforms from two promoters by alternative splicing. To characterize the transcriptional capacities of all 12 HNF4α isoforms, stable lines expressing each isoform were generated. The entire transcriptome associated with each isoform was analyzed as well as their respective interacting proteome. Major differences were noted in the transcriptional function of these isoforms. The α1 and α2 isoforms were the strongest regulators of gene expression whereas the α3 isoform exhibited significantly reduced activity. The α4, α5, and α6 isoforms, which use an alternative first exon, were characterized for the first time, and showed a greatly reduced transcriptional potential with an inability to recognize the consensus response element of HNF4α. Several transcription factors and coregulators were identified as potential specific partners for certain HNF4α isoforms. An analysis integrating the vast amount of omics data enabled the identification of transcriptional regulatory mechanisms specific to certain HNF4α isoforms, hence demonstrating the importance of considering all isoforms given their seemingly diverse functions.

The respiratory epithelium comprises polarized cells at the interface between the environment and airway tissues. Polarized apical and basolateral protein secretions are a feature of airway epithelium homeostasis. Human respiratory syncytial virus (hRSV) is a major human pathogen that primarily targets the respiratory epithelium. However, the consequences of hRSV infection on epithelium secretome polarity and content remain poorly understood. To investigate the hRSV-associated apical and basolateral secretomes, a proteomics approach was combined with an ex vivo pediatric human airway epithelial (HAE) model of hRSV infection (data are available via ProteomeXchange and can be accessed at https://www.ebi.ac.uk/pride/ with identifier PXD013661). Following infection, a skewing of apical/basolateral abundance ratios was identified for several individual proteins. Novel modulators of neutrophil and lymphocyte activation (CXCL6, CSF3, SECTM1 or CXCL16), and antiviral proteins (BST2 or CEACAM1) were detected in infected, but not in uninfected cultures. Importantly, CXCL6, CXCL16, CSF3 were also detected in nasopharyngeal aspirates (NPA) from hRSV-infected infants but not healthy controls. Furthermore, the antiviral activity of CEACAM1 against RSV was confirmed in vitro using BEAS-2B cells. hRSV infection disrupted the polarity of the pediatric respiratory epithelial secretome and was associated with immune modulating proteins (CXCL6, CXCL16, CSF3) never linked with this virus before. In addition, the antiviral activity of CEACAM1 against hRSV had also never been previously characterized. This study, therefore, provides novel insights into RSV pathogenesis and endogenous antiviral responses in pediatric airway epithelium.

Autoimmune thyroid diseases (AITD) are the most common group of autoimmune diseases, associated with lymphocyte infiltration and the production of thyroid autoantibodies, like thyroid peroxidase antibodies (TPOAb), in the thyroid gland. Immunoglobulins and cell-surface receptors are glycoproteins with distinctive glycosylation patterns that play a structural role in maintaining and modulating their functions. We investigated associations of total circulating IgG and peripheral blood mononuclear cells glycosylation with AITD and the influence of genetic background in a case-control study with several independent cohorts and over 3,000 individuals in total. The study revealed an inverse association of IgG core fucosylation with TPOAb and AITD, as well as decreased peripheral blood mononuclear cells antennary α1,2 fucosylation in AITD, but no shared genetic variance between AITD and glycosylation. These data suggest that the decreased level of IgG core fucosylation is a risk factor for AITD that promotes antibody-dependent cell-mediated cytotoxicity previously associated with TPOAb levels.

The study of protein subcellular distribution, their assembly into complexes and the set of proteins with which they interact with is essential to our understanding of fundamental biological processes. Complementary to traditional assays, proximity-dependent biotinylation (PDB) approaches coupled with mass spectrometry (such as BioID or APEX) have emerged as powerful techniques to study proximal protein interactions and the subcellular proteome in the context of living cells and organisms. Since their introduction in 2012, PDB approaches have been used in an increasing number of studies and the enzymes themselves have been subjected to intensive optimization. How these enzymes have been optimized and considerations for their use in proteomics experiments are important questions. Here, we review the structural diversity and mechanisms of the two main classes of PDB enzymes: the biotin protein ligases (BioID) and the peroxidases (APEX). We describe the engineering of these enzymes for PDB and review emerging applications, including the development of PDB for coincidence detection (split-PDB). Lastly, we briefly review enzyme selection and experimental design guidelines and reflect on the labeling chemistries and their implication for data interpretation.

Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across cells in a tissue because of many sources of cellular genetic and non-genetic variance. Signaling network heterogeneity is the key to many biological processes, such as cell differentiation and drug resistance. Only recently, the emergence of multiplexed single-cell measurement technologies has made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of each type of technology. We also describe the available computational tools for network characterization using single-cell data and discuss potential confounding factors that need to be considered in single-cell signaling network analyses.

Pyruvate kinase muscle isoform 2 (PKM2) is a key glycolytic enzyme involved in ATP generation and critical for cancer metabolism. PKM2 is expressed in many human cancers and is regulated by complex mechanisms that promote tumor growth and proliferation. Therefore, it is considered an attractive therapeutic target for modulating tumor metabolism. Various stimuli allosterically regulate PKM2 by cycling it between highly active and less active states. Several small molecules activate PKM2 by binding to its intersubunit interface. Serine and cysteine serve as an activator and inhibitor of PKM2, respectively, by binding to its amino acid (AA)-binding pocket, which therefore represents a potential druggable site. Despite binding similarly to PKM2, how cysteine and serine differentially regulate this enzyme remains elusive. Using kinetic analyses, fluorescence binding, X-ray crystallography, and gel filtration experiments with asparagine, aspartate, and valine as PKM2 ligands, we examined whether the differences in the side-chain polarity of these AAs trigger distinct allosteric responses in PKM2. We found that Asn (polar) and Asp (charged) activate PKM2 and that Val (hydrophobic) inhibits it. The results also indicate that both Asn and Asp can restore the activity of Val-inhibited PKM2. AA-bound crystal structures of PKM2 displayed distinctive interactions within the binding pocket, causing unique allosteric effects in the enzyme. These structure-function analyses of AA-mediated PKM2 regulation shed light on the chemical requirements in the development of mechanism-based small-molecule modulators targeting the AA-binding pocket of PKM2 and provide broader insights into the regulatory mechanisms of complex allosteric enzymes.