Sudhir Gopal Tattikota

Bio: Sudhir Gopal Tattikota is an academic researcher from Harvard University. The author has contributed to research in topics: Cell type & microRNA. The author has an hindex of 14, co-authored 28 publications receiving 1350 citations. Previous affiliations of Sudhir Gopal Tattikota include Max Delbrück Center for Molecular Medicine.

NetPath: a public resource of curated signal transduction pathways

Abstract: We have developed NetPath as a resource of curated human signaling pathways. As an initial step, NetPath provides detailed maps of a number of immune signaling pathways, which include approximately 1,600 reactions annotated from the literature and more than 2,800 instances of transcriptionally regulated genes - all linked to over 5,500 published articles. We anticipate NetPath to become a consolidated resource for human signaling pathways that should enable systems biology approaches.

A curated compendium of phosphorylation motifs.

Abstract: To the editor: Protein phosphorylation is a covalent posttranslational modification event that is essential for regulation and maintenance of most biological processes in eukaryotes1. Conventionally, phosphorylation sites have been discovered using biochemical experiments with the sequence contexts or ‘motifs’ generally defined by manually aligning the sequences of phosphorylated peptides. Today, high-throughput methods, such as tandem mass spectrometry, allow rapid and directed discovery of hundreds of phosphorylation sites in a single experiment, which necessitates analysis of the ‘motifs’ in the identified phosphopeptides. Until now, however, there has been no single resource that allows investigators to determine whether a protein/peptide of interest contains a motif that has been previously described in the literature. We describe below a publicly available catalog of phosphorylation motifs that we have created for the community (http://www.hprd.org/PhosphoMotif_finder). In higher eukaryotes, phosphorylation occurs on serine, threonine and tyrosine residues. Dysregulation of phosphorylation and dephosphorylation events is associated with several diseases and malignancies in humans. The determinants of specificity for kinases are not well understood, although it is understood that both the amino acid sequence motif surrounding the serine/ threonine/tyrosine residues and the threedimensional structure of the substrate proteins contribute to the specificity. The surrounding sequence context, or motif, is in turn responsible for the binding of downstream proteins containing modular phosphoprotein-binding domains. For example, tyrosine phosphorylated proteins have been shown to bind to Src homology 2 (SH2) and phosphotyrosine binding (PTB) domains2, whereas serine/threonine phosphorylated proteins have been described to bind to WW (two conserved tryptophans), Forkhead, WD40 or 14-3-3 domaincontaining proteins3. Although several prediction programs for phosphorylation motifs are available4–8, they do not always offer a simple ‘mapping’ of all literature-based motifs onto test sequences. For example, Scansite5 is one resource that predicts short protein sequence motifs that can be recognized by signaling domains or phosphorylated by protein serine/threonine/tyrosine kinases on the basis of results from oriented peptide library and phage display experiments. In addition, NetPhos8 and KinasePhos7 predict kinase phosphorylation sites in protein sequences based on a data set of known phosphorylation sites. Phospho.ELM9 and Phosphosite are databases that contain a list of experimentally determined phosphorylation sites. Significantly, these resources neither provide a listing of consensus motifs nor the exact algorithm used for prediction of motifs. To ensure identification of well-described motifs in any test sequence, one must also go through abstracts of PubMed articles where such motifs have been described—not a trivial task given that there are >130,000 published articles containing the term ‘phosphorylation’. Furthermore, the abstracts of most of these papers do not mention if any motif is described or provide the sequence of the motif itself, which precludes automated data mining. We have assembled a compendium of 324 known phosphorylation motifs based on the literature. These motifs have been categorized as (i) phosphorylation-based substrate motifs (that is, motifs that are recognized by serine/threonine/tyrosine kinases or phosphatases and (ii) phosphorylationbased binding motifs (that is, motifs that get phosphorylated and act as molecular scaffolds for binding to domains that specifically bind to phosphorylated serine/threonine/tyrosine residues). Supplementary Table 1 online lists 132 phosphotyrosine-based motifs, whereas Supplementary Table 2 online lists 192 phosphoserine/phosphothreonine-based motifs. Original research articles describing the motif are linked to each motif. These include 24 phosphatase substrate motifs and 80 motifs that bind to domains recognizing phosphorylated serine/threonine/tyrosine residues. Tyrosine kinases and tyrosine phosphatases, as well as SH2 and PTB domains, have been investigated in some detail over the past several years. This is both because of their relevance to growth factor–receptor signaling and the availability of good antiphosphotyrosine antibodies as tools to dissect phosphotyrosine-mediated interactions and pathways. In this compendium, we have catalogued 132 phosphotyrosine-based motifs consisting of 50 tyrosine kinase substrate motifs, 19 tyrosine phosphatase substrate motifs, 56 SH2 domain and 7 PTB domain-binding motifs (Supplementary Table 1). Serine/threonine kinases phosphorylate proteins on serine/threonine residues to regulate the activity of the proteins as well as to make them available for binding to 14-3-3 proteins, WW-binding domains and Forkhead-associated (FHA), WD40 and PBD domains. We have catalogued 192 serine/threonine phosphorylation-based motifs consisting of 170 serine/threonine kinase substrate motifs, 5 serine/threonine phosphatase substrate motifs and 17 motifs that mediate binding to serine/threonine binding proteins (Supplementary Table 2). To make the list of phosphorylation motifs easily accessible to the community, we have also developed a search tool designated ‘PhosphoMotif Finder’, which we incorporated into the Human Protein Reference Database developed earlier by

Fly Cell Atlas: A single-nucleus transcriptomic atlas of the adult fruit fly

Abstract: For more than 100 years, the fruit fly Drosophila melanogaster has been one of the most studied model organisms. Here, we present a single-cell atlas of the adult fly, Tabula Drosophilae, that includes 580,000 nuclei from 15 individually dissected sexed tissues as well as the entire head and body, annotated to >250 distinct cell types. We provide an in-depth analysis of cell type–related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types between tissues, such as blood and muscle cells, reveals rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the Drosophila community and serves as a reference to study genetic perturbations and disease models at single-cell resolution. Description Cell type diversity in a whole fly The fruit fly Drosophila melanogaster has served as a premier model organism for discovering fundamental and evolutionarily conserved biological mechanisms. Combining recent advances in single-cell sequencing with powerful fly genetic tools holds great promise for making further discoveries. Li et al. present a single-cell atlas of the entire adult fly that includes 580,000 cells and more than 250 annotated cell types. Cells from the head and body recapitulated cell types from 15 dissected tissues. In-depth analyses revealed rare cell types, cell-type-specific gene signatures, and sexual dimorphism. This atlas provides a resource for the Drosophila community to study genetic perturbations and diseases at single-cell resolution. —BAP A single-nucleus transcriptomic map reveals more than 250 distinct cell types in the entire adult Drosophila melanogaster. INTRODUCTION Drosophila melanogaster has had a fruitful history in biological research because it has contributed to many key discoveries in genetics, development, and neurobiology. The fruit fly genome contains ~14,000 protein-coding genes, ~63% of which have human orthologs. Single-cell RNA-sequencing has recently been applied to multiple Drosophila tissues and developmental stages. However, these data have been generated by different laboratories on different genetic backgrounds with different dissociation protocols and sequencing platforms, which has hindered the systematic comparison of gene expression across cells and tissues. RATIONALE We aimed to establish a cell atlas for the entire adult Drosophila with the same genetic background, dissociation protocol, and sequencing platform to (i) obtain a comprehensive categorization of cell types, (ii) integrate single-cell transcriptome data with existing knowledge about gene expression and cell types, (iii) systematically compare gene expression across the entire organism and between males and females, and (iv) identify cell type–specific markers across the entire organism. We chose single-nucleus RNA-sequencing (snRNA-seq) to circumvent the difficulties of dissociating cells that are embedded in the cuticle (e.g., sensory neurons) or that are multinucleated (e.g., muscle cells). We took two complementary strategies: sequencing nuclei from dissected tissues to know the identity of the tissue source and sequencing nuclei from the entire head and body to ensure that all cells are sampled. Experts from 40 laboratories participated in crowd annotation to assign transcriptomic cell types with the best knowledge available. RESULTS We sequenced 570,000 cells using droplet-based 10x Genomics from 15 dissected tissues as well as whole heads and bodies, separately in females and males. We also sequenced 10,000 cells from dissected tissues using the plate-based Smart-seq2 platform, providing deeper coverage per cell. We developed reproducible analysis pipelines using NextFlow and implemented a distributed cell-type annotation system with controlled vocabularies in SCope. Crowd-based annotations of transcriptomes from dissected tissues identified 17 main cell categories and 251 detailed cell types linked to FlyBase ontologies. Many of these cell types are characterized for the first time, either because they emerged only after increasing cell coverage or because they reside in tissues that had not been previously subjected to scRNA-seq. The excellent correspondence of transcriptomic clusters from whole body and dissected tissues allowed us to transfer annotations and identify a few cuticular cell types not detected in individual tissues. Cross-tissue analysis revealed location-specific subdivisions of muscle cells and heterogeneity within blood cells. We then determined cell type–specific marker genes and transcription factors with different specificity levels, enabling the construction of gene regulatory networks. Finally, we explored sexual dimorphism, finding a link between sex-biased expression and the presence of doublesex, and investigated tissue dynamics through trajectory analyses. CONCLUSION Our Fly Cell Atlas (FCA) constitutes a valuable resource for the Drosophila community as a reference for studies of gene function at single-cell resolution. All the FCA data are freely available for further analysis through multiple portals and can be downloaded for custom analyses using other single-cell tools. The ability to annotate cell types by sequencing the entire head and body will facilitate the use of Drosophila in the study of biological processes and in modeling human diseases at a whole-organism level with cell-type resolution. All data with annotations can be accessed from www.flycellatlas.org, which provides links to SCope, ASAP, and cellxgene portals. Tabula Drosophilae. In this single-cell atlas of the adult fruit fly, 580,000 cells were sequenced and >250 cell types were annotated. They are from 15 individually dissected sexed tissues as well as the entire head and body. All data are freely available for visualization and download, with featured analyses shown at the bottom right.

A cell atlas of the adult Drosophila midgut.

Abstract: Studies of the adult Drosophila midgut have led to many insights in our understanding of cell-type diversity, stem cell regeneration, tissue homeostasis, and cell fate decision. Advances in single-cell RNA sequencing provide opportunities to identify new cell types and molecular features. We used single-cell RNA sequencing to characterize the transcriptome of midgut epithelial cells and identified 22 distinct clusters representing intestinal stem cells, enteroblasts, enteroendocrine cells (EEs), and enterocytes. This unbiased approach recovered most of the known intestinal stem cells/enteroblast and EE markers, highlighting the high quality of the dataset, and led to insights on intestinal stem cell biology, cell type-specific organelle features, the roles of new transcription factors in progenitors and regional variation along the gut, 5 additional EE gut hormones, EE hormonal expression diversity, and paracrine function of EEs. To facilitate mining of this rich dataset, we provide a web-based resource for visualization of gene expression in single cells. Altogether, our study provides a comprehensive resource for addressing functions of genes in the midgut epithelium.

Human Protein Reference Database—2009 update

Abstract: Human Protein Reference Database (HPRD--http://www.hprd.org/), initially described in 2003, is a database of curated proteomic information pertaining to human proteins. We have recently added a number of new features in HPRD. These include PhosphoMotif Finder, which allows users to find the presence of over 320 experimentally verified phosphorylation motifs in proteins of interest. Another new feature is a protein distributed annotation system--Human Proteinpedia (http://www.humanproteinpedia.org/)--through which laboratories can submit their data, which is mapped onto protein entries in HPRD. Over 75 laboratories involved in proteomics research have already participated in this effort by submitting data for over 15,000 human proteins. The submitted data includes mass spectrometry and protein microarray-derived data, among other data types. Finally, HPRD is also linked to a compendium of human signaling pathways developed by our group, NetPath (http://www.netpath.org/), which currently contains annotations for several cancer and immune signaling pathways. Since the last update, more than 5500 new protein sequences have been added, making HPRD a comprehensive resource for studying the human proteome.

TFEB links autophagy to lysosomal biogenesis.

Abstract: Autophagy is a cellular catabolic process that relies on the cooperation of autophagosomes and lysosomes. During starvation, the cell expands both compartments to enhance degradation processes. We found that starvation activates a transcriptional program that controls major steps of the autophagic pathway, including autophagosome formation, autophagosome-lysosome fusion, and substrate degradation. The transcription factor EB (TFEB), a master gene for lysosomal biogenesis, coordinated this program by driving expression of autophagy and lysosomal genes. Nuclear localization and activity of TFEB were regulated by serine phosphorylation mediated by the extracellular signal-regulated kinase 2, whose activity was tuned by the levels of extracellular nutrients. Thus, a mitogen-activated protein kinase-dependent mechanism regulates autophagy by controlling the biogenesis and partnership of two distinct cellular organelles.

Integrative Genomics Viewer

Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Association analysis identifies 65 new breast cancer risk loci

Abstract: Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.