Pier Federico Gherardini

Highly multiplexed simultaneous detection of RNAs and proteins in single cells

To enable the detection of expression signatures specific to individual cells, we developed PLAYR (proximity ligation assay for RNA), a method for highly multiplexed transcript quantification by flow and mass cytometry that is compatible with standard antibody staining. When used with mass cytometry, PLAYR allowed for the simultaneous quantification of more than 40 different mRNAs and proteins. In primary cells, we quantified multiple transcripts, with the identity and functional state of each analyzed cell defined on the basis of the expression of a separate set of transcripts or proteins. By expanding high-throughput deep phenotyping of cells beyond protein epitopes to include RNA expression, PLAYR opens a new avenue for the characterization of cellular metabolism.

An interactive reference framework for modeling a dynamic immune system

Single-cell measurements map immunity Multiple characteristics of individual cells define cell types and their physiological states. Spitzer et al. quantitated the abundance of 39 different cell surface proteins or transcription factors on individual cells of the mouse immune system. They used these measurements to create a map that clustered similar individual cells into groups corresponding to cell type and function. Their extensible experimental platform will allow the inclusion of other data types and data from independent laboratories. Science, this issue 10.1126/science.1259425 Cytometry meets mass spectrometry to create a functional map of the immune system. INTRODUCTION Immune cells constitute an interacting hierarchy that coordinates its activities according to genetic and environmental contexts. This systemically mobile network of cells results in emergent properties that are derived from dynamic cellular interactions. Unlike many solid tissues, where cells of given functions are localized into substructures that can be readily defined, the distribution of phenotypically similar immune cells into various organs complicates discerning any modest differences between them. Over decades of investigation into immune functions during health and disease, research has necessarily focused on understanding the individual cell types within the immune system, and, more recently, toward identifying interacting cells and the messengers they use to communicate. RATIONALE Methods of single-cell analysis, such as flow cytometry, have led the effort to enumerate and quantitatively characterize immune cell populations. As research has accelerated, our understanding of immune organization has surpassed the technical limitations of fluorescence-based flow cytometry. With the advent of mass cytometry, which enables measuring significantly more features of individual cells, most known immune cell types can now be identified from within a single experiment. Leveraging this capability, we set out to initiate an immune system reference framework to provide a working definition of immune organization and enable the integration of new data sets. RESULTS To build a reference framework from mass cytometry data, we developed a novel algorithm to transform the single-cell data into intuitive maps. These Scaffold maps provide a data-driven interpretation of immune organization while also integrating conventional immune cell populations as landmarks to orient the user. By applying Scaffold maps to data from the bone marrow of wild-type C57BL/6 mice, the method reconstructed the organization within this complex developmental organ. Using this sample as a reference point, the unique organization of immune cells within various organs across the body was revealed. The maps recapitulated canonical cellular phenotypes while revealing reproducible, tissue-specific deviations. The approach revealed influences of genetic variation and circadian rhythms on immune structure, permitted direct comparisons of murine and human blood cell phenotypes, and even enabled archival fluorescence-based flow cytometry data to be mapped onto the reference framework. CONCLUSION This foundational reference map provides a working definition of systemic immune organization to which new data can be integrated to reveal deviations driven by genetics, environment, or pathology. Beyond providing an analytical framework to understand immune organization from the unified data set generated here, the approaches we describe can serve as a data repository for collating experimental data from the research community, including gene expression and mutational analysis. Efforts that characterize cellular behavior in this open-source approach will continue to improve upon the initiating reference presented here to reveal the inherent structure in biological networks of immunity for clinical benefit. Building a dynamic immune system reference framework. By combining mass cytometry with the Scaffold maps algorithm, the cellular organization of any complex sample can be transformed into an intuitive and interactive map for further analysis. By first choosing one foundational sample as a reference (i.e., the bone marrow of wild-type mice), the effects of any perturbation can be readily identified in this framework. Immune cells function in an interacting hierarchy that coordinates the activities of various cell types according to genetic and environmental contexts. We developed graphical approaches to construct an extensible immune reference map from mass cytometry data of cells from different organs, incorporating landmark cell populations as flags on the map to compare cells from distinct samples. The maps recapitulated canonical cellular phenotypes and revealed reproducible, tissue-specific deviations. The approach revealed influences of genetic variation and circadian rhythms on immune system structure, enabled direct comparisons of murine and human blood cell phenotypes, and even enabled archival fluorescence-based flow cytometry data to be mapped onto the reference framework. This foundational reference map provides a working definition of systemic immune organization to which new data can be integrated to reveal deviations driven by genetics, environment, or pathology.

AMBRA1 links autophagy to cell proliferation and tumorigenesis by promoting c-Myc dephosphorylation and degradation

Inhibition of a main regulator of cell metabolism, the protein kinase mTOR, induces autophagy and inhibits cell proliferation. However, the molecular pathways involved in the cross-talk between these two mTOR-dependent cell processes are largely unknown. Here we show that the scaffold protein AMBRA1, a member of the autophagy signalling network and a downstream target of mTOR, regulates cell proliferation by facilitating the dephosphorylation and degradation of the proto-oncogene c-Myc. We found that AMBRA1 favours the interaction between c-Myc and its phosphatase PP2A and that, when mTOR is inhibited, it enhances PP2A activity on this specific target, thereby reducing the cell division rate. As expected, such a de-regulation of c-Myc correlates with increased tumorigenesis in AMBRA1-defective systems, thus supporting a role for AMBRA1 as a haploinsufficient tumour suppressor gene.

Structure-based function prediction: approaches and applications

The ever increasing number of protein structures determined by structural genomic projects has spurred much interest in the development of methods for structure-based function prediction. Existing methods can be roughly classified in two groups: some use a comparative approach looking for the presence of structural motifs possibly associated with a known biochemical function. Other methods try to identify functional patches on the surface of a protein using only its physicochemical characteristics. This review will cover both kinds of approaches to structure-based function prediction as well as their use in real-world cases. The main issues and limitations in using protein structure to predict function will also be discussed. These are mainly: the assessment of the statistical significance of structural similarities and the extent to which these methods depend on the accuracy and availability of structural data.

Exploring the diversity of SPRY/B30.2-mediated interactions

The SPla/Ryanodine receptor (SPRY)/B30.2 domain is one of the most common folds in higher eukaryotes. The human genome encodes 103 SPRY/B30.2 domains, several of which are involved in the immune response. Approximately 45% of human SPRY/B30.2-containing proteins are E3 ligases. The role and function of the majority of SPRY/B30.2 domains are still poorly understood, however, in several cases mutations in this domain have been linked to congenital disorders. The recent characterization of SPRY/B30.2-mediated protein interactions has provided evidence for a role of this domain as an adaptor module to assemble macromolecular complexes, analogous to Src homology (SH)2, SH3, and WW domains. However, functional and structural evidence suggests that SPRY/B30.2 is a more versatile fold, allowing a wide range of binding modes.

Identification of Leishmania-specific protein phosphorylation sites by LC-ESI-MS/MS and comparative genomics analyses.

Human pathogenic protozoa of the genus Leishmania undergo various developmental transitions during the infectious cycle that are triggered by changes in the host environment. How these parasites sense, transduce, and respond to these signals is only poorly understood. Here we used phosphoproteomic approaches to monitor signaling events in L. donovani axenic amastigotes, which may be important for intracellular parasite survival. LC‐ESI‐MS/MS analysis of IMAC‐enriched phosphoprotein extracts identified 445 putative phosphoproteins in two independent biological experiments. Functional enrichment analysis allowed us to gain insight into parasite pathways that are regulated by protein phosphorylation and revealed significant enrichment in our data set of proteins whose biological functions are associated with protein turn‐over, stress response, and signal transduction. LC‐ESI‐MS/MS analysis of TiO2‐enriched phosphopeptides confirmed these results and identified 157 unique phosphopeptides covering 181 unique phosphorylation sites in 126 distinct proteins. Investigation of phosphorylation site conservation across related trypanosomatids and higher eukaryotes by multiple sequence alignment and cluster analysis revealed L. donovani‐specific phosphoresidues in highly conserved proteins that share significant sequence homology to orthologs of the human host. These unique phosphorylation sites reveal important differences between host and parasite biology and post‐translational protein regulation, which may be exploited for the design of novel anti‐parasitic interventions.

FunClust: a web server for the identification of structural motifs in a set of non-homologous protein structures

BackgroundThe occurrence of very similar structural motifs brought about by different parts of non homologous proteins is often indicative of a common function. Indeed, relatively small local structures can mediate binding to a common partner, be it a protein, a nucleic acid, a cofactor or a substrate. While it is relatively easy to identify short amino acid or nucleotide sequence motifs in a given set of proteins or genes, and many methods do exist for this purpose, much more challenging is the identification of common local substructures, especially if they are formed by non consecutive residues in the sequence.ResultsHere we describe a publicly available tool, able to identify common structural motifs shared by different non homologous proteins in an unsupervised mode. The motifs can be as short as three residues and need not to be contiguous or even present in the same order in the sequence. Users can submit a set of protein structures deemed or not to share a common function (e.g. they bind similar ligands, or share a common epitope). The server finds and lists structural motifs composed of three or more spatially well conserved residues shared by at least three of the submitted structures. The method uses a local structural comparison algorithm to identify subsets of similar amino acids between each pair of input protein chains and a clustering procedure to group similarities shared among different structure pairs.ConclusionsFunClust is fast, completely sequence independent, and does not need an a priori knowledge of the motif to be found. The output consists of a list of aligned structural matches displayed in both tabular and graphical form. We show here examples of its usefulness by searching for the largest common structural motifs in test sets of non homologous proteins and showing that the identified motifs correspond to a known common functional feature.

Phospho3D: a database of three-dimensional structures of protein phosphorylation sites

Phosphorylation is the most common protein post-translational modification. Phosphorylated residues (serine, threonine and tyrosine) play critical roles in the regulation of many cellular processes. Since the amount of data produced by screening assays is growing continuously, the development of computational tools for collecting and analysing experimental data has become a pivotal task for unravelling the complex network of interactions regulating eukaryotic cell life. Here we present Phospho3D, , a database of 3D structures of phosphorylation sites, which stores information retrieved from the phospho.ELM database and is enriched with structural information and annotations at the residue level. The database also collects the results of a large-scale structural comparison procedure providing clues for the identification of new putative phosphorylation sites.

Phospho3D 2.0: an enhanced database of three-dimensional structures of phosphorylation sites

Phospho3D is a database of three-dimensional (3D) structures of phosphorylation sites (P-sites) derived from the Phospho.ELM database, which also collects information on the residues surrounding the P-site in space (3D zones). The database also provides the results of a large-scale structural comparison of the 3D zones versus a representative dataset of structures, thus associating to each P-site a number of structurally similar sites. The new version of Phospho3D presents an 11-fold increase in the number of 3D sites and incorporates several additional features, including new structural descriptors, the possibility of selecting non-redundant sets of 3D structures and the availability for download of non-redundant sets of structurally annotated P-sites. Moreover, it features P3Dscan, a new functionality that allows the user to submit a protein structure and scan it against the 3D zones collected in the Phospho3D database. Phospho3D version 2.0 is available at: http://www.phospho3d.org/.

Single-cell systems-level analysis of human Toll-like receptor activation defines a chemokine signature in patients with systemic lupus erythematosus

BACKGROUND Activation of Toll-like receptors (TLRs) induces inflammatory responses involved in immunity to pathogens and autoimmune pathogenesis, such as in patients with systemic lupus erythematosus (SLE). Although TLRs are differentially expressed across the immune system, a comprehensive analysis of how multiple immune cell subsets respond in a system-wide manner has not been described. OBJECTIVE We sought to characterize TLR activation across multiple immune cell subsets and subjects, with the goal of establishing a reference framework against which to compare pathologic processes. METHODS Peripheral whole-blood samples were stimulated with TLR ligands and analyzed by means of mass cytometry simultaneously for surface marker expression, activation states of intracellular signaling proteins, and cytokine production. We developed a novel data visualization tool to provide an integrated view of TLR signaling networks with single-cell resolution. We studied 17 healthy volunteer donors and 8 patients with newly diagnosed and untreated SLE. RESULTS Our data revealed the diversity of TLR-induced responses within cell types, with TLR ligand specificity. Subsets of natural killer cells and T cells selectively induced nuclear factor κ light chain enhancer of activated B cells in response to TLR2 ligands. CD14(hi) monocytes exhibited the most polyfunctional cytokine expression patterns, with more than 80 distinct cytokine combinations. Monocytic TLR-induced cytokine patterns were shared among a group of healthy donors, with minimal intraindividual and interindividual variability. Furthermore, autoimmune disease altered baseline cytokine production; newly diagnosed untreated SLE patients shared a distinct monocytic chemokine signature, despite clinical heterogeneity. CONCLUSION Mass cytometry defined a systems-level reference framework for human TLR activation, which can be applied to study perturbations in patients with inflammatory diseases, such as SLE.