Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens.

BACKGROUND: Drug targets with genetic evidence are expected to increase clinical success by at least twofold. Yet, translating disease-associated genetic variants into functional knowledge remains a fundamental challenge of drug discovery. A key issue is that the vast majority of complex disease associations cannot be cleanly mapped to a gene. Immune disease-associated variants are enriched within regulatory elements found in T-cell-specific open chromatin regions. RESULTS: To identify genes and molecular programs modulated by these regulatory elements, we develop a CRISPRi-based single-cell functional screening approach in primary human T cells. Our pipeline enables the interrogation of transcriptomic changes induced by the perturbation of regulatory elements at scale. We first optimize an efficient CRISPRi protocol in primary CD4+ T cells via CROPseq vectors. Subsequently, we perform a screen targeting 45 non-coding regulatory elements and 35 transcription start sites and profile approximately 250,000 T -cell single-cell transcriptomes. We develop a bespoke analytical pipeline for element-to-gene (E2G) mapping and demonstrate that our method can identify both previously annotated and novel E2G links. Lastly, we integrate genetic association data for immune-related traits and demonstrate how our platform can aid in the identification of effector genes for GWAS loci. CONCLUSIONS: We describe "primary T cell crisprQTL" - a scalable, single-cell functional genomics approach for mapping regulatory elements to genes in primary human T cells. We show how this framework can facilitate the interrogation of immune disease GWAS hits and propose that the combination of experimental and QTL-based techniques is likely to address the variant-to-function problem.

Decoding Heterogenous Single-cell Perturbation Responses.

Understanding diverse responses of individual cells to the same perturbation is central to many biological and biomedical problems. Current methods, however, do not precisely quantify the strength of perturbation responses and, more importantly, reveal new biological insights from heterogeneity in responses. Here we introduce the perturbation-response score (PS), based on constrained quadratic optimization, to quantify diverse perturbation responses at a single-cell level. Applied to single-cell transcriptomes of large-scale genetic perturbation datasets (e.g., Perturb-seq), PS outperforms existing methods for quantifying partial gene perturbation responses. In addition, PS presents two major advances. First, PS enables large-scale, single-cell-resolution dosage analysis of perturbation, without the need to titrate perturbation strength. By analyzing the dose-response patterns of over 2,000 essential genes in Perturb-seq, we identify two distinct patterns, depending on whether a moderate reduction in their expression induces strong downstream expression alterations. Second, PS identifies intrinsic and extrinsic biological determinants of perturbation responses. We demonstrate the application of PS in contexts such as T cell stimulation, latent HIV-1 expression, and pancreatic cell differentiation. Notably, PS unveiled a previously unrecognized, cell-type-specific role of coiled-coil domain containing 6 (CCDC6) in guiding liver and pancreatic lineage decisions, where CCDC6 knockouts drive the endoderm cell differentiation towards liver lineage, rather than pancreatic lineage. The PS approach provides an innovative method for dose-to-function analysis and will enable new biological discoveries from single-cell perturbation datasets.

Next-generation sequencing of a combinatorial peptide phage library screened against ubiquitin identifies peptide aptamers that can inhibit the in vitro ubiquitin transfer cascade.

Defining dynamic protein-protein interactions in the ubiquitin conjugation reaction is a challenging research area. Generating peptide aptamers that target components such as ubiquitin itself, E1, E2, or E3 could provide tools to dissect novel features of the enzymatic cascade. Next-generation deep sequencing platforms were used to identify peptide sequences isolated from phage-peptide libraries screened against Ubiquitin and its ortholog NEDD8. In over three rounds of selection under differing wash criteria, over 13,000 peptides were acquired targeting ubiquitin, while over 10,000 peptides were selected against NEDD8. The overlap in peptides against these two proteins was less than 5% suggesting a high degree in specificity of Ubiquitin or NEDD8 toward linear peptide motifs. Two of these ubiquitin-binding peptides were identified that inhibit both E3 ubiquitin ligases MDM2 and CHIP. NMR analysis highlighted distinct modes of binding of the two different peptide aptamers. These data highlight the utility of using next-generation sequencing of combinatorial phage-peptide libraries to isolate peptide aptamers toward a protein target that can be used as a chemical tool in a complex multi-enzyme reaction.

Identification of AGR2 Gene-Specific Expression Patterns Associated with Epithelial-Mesenchymal Transition.

The TGF-ß signaling pathway is involved in numerous cellular processes, and its deregulation may result in cancer development. One of the key processes in tumor progression and metastasis is epithelial to mesenchymal transition (EMT), in which TGF-ß signaling plays important roles. Recently, AGR2 was identified as a crucial component of the cellular machinery responsible for maintaining the epithelial phenotype, thereby interfering with the induction of mesenchymal phenotype cells by TGF-ß effects in cancer. Here, we performed transcriptomic profiling of A549 lung cancer cells with CRISPR-Cas9 mediated AGR2 knockout with and without TGF-ß treatment. We identified significant changes in transcripts associated with focal adhesion and eicosanoid production, in particular arachidonic acid metabolism. Changes in transcripts associated with the focal adhesion pathway were validated by RT-qPCR of COL4A1, COL4A2, FLNA, VAV3, VEGFA, and VINC mRNAs. In addition, immunofluorescence showed the formation of stress fibers and vinculin foci in cells without AGR2 and in response to TGF-ß treatment, with synergistic effects observed. These findings imply that both AGR2 downregulation and TGF-ß have a role in focal adhesion formation and cancer cell migration and invasion. Transcripts associated with arachidonic acid metabolism were downregulated after both AGR2 knockout and TGF-ß treatment and were validated by RT-qPCR of GPX2, PTGS2, and PLA2G4A. Since PGE2 is a product of arachidonic acid metabolism, its lowered concentration in media from AGR2-knockout cells was confirmed by ELISA. Together, our results demonstrate that AGR2 downregulation and TGF-ß have an essential role in focal adhesion formation; moreover, we have identified AGR2 as an important component of the arachidonic acid metabolic pathway.

Standardized next-generation sequencing of immunoglobulin and T-cell receptor gene recombinations for MRD marker identification in acute lymphoblastic leukaemia; a EuroClonality-NGS validation study.

Amplicon-based next-generation sequencing (NGS) of immunoglobulin (IG) and T-cell receptor (TR) gene rearrangements for clonality assessment, marker identification and quantification of minimal residual disease (MRD) in lymphoid neoplasms has been the focus of intense research, development and application. However, standardization and validation in a scientifically controlled multicentre setting is still lacking. Therefore, IG/TR assay development and design, including bioinformatics, was performed within the EuroClonality-NGS working group and validated for MRD marker identification in acute lymphoblastic leukaemia (ALL). Five EuroMRD ALL reference laboratories performed IG/TR NGS in 50 diagnostic ALL samples, and compared results with those generated through routine IG/TR Sanger sequencing. A central polytarget quality control (cPT-QC) was used to monitor primer performance, and a central in-tube quality control (cIT-QC) was spiked into each sample as a library-specific quality control and calibrator. NGS identified 259 (average 5.2/sample, range 0-14) clonal sequences vs. Sanger-sequencing 248 (average 5.0/sample, range 0-14). NGS primers covered possible IG/TR rearrangement types more completely compared with local multiplex PCR sets and enabled sequencing of bi-allelic rearrangements and weak PCR products. The cPT-QC showed high reproducibility across all laboratories. These validated and reproducible quality-controlled EuroClonality-NGS assays can be used for standardized NGS-based identification of IG/TR markers in lymphoid malignancies.

Quality control and quantification in IG/TR next-generation sequencing marker identification: protocols and bioinformatic functionalities by EuroClonality-NGS.

Assessment of clonality, marker identification and measurement of minimal residual disease (MRD) of immunoglobulin (IG) and T cell receptor (TR) gene rearrangements in lymphoid neoplasms using next-generation sequencing (NGS) is currently under intensive development for use in clinical diagnostics. So far, however, there is a lack of suitable quality control (QC) options with regard to standardisation and quality metrics to ensure robust clinical application of such approaches. The EuroClonality-NGS Working Group has therefore established two types of QCs to accompany the NGS-based IG/TR assays. First, a central polytarget QC (cPT-QC) is used to monitor the primer performance of each of the EuroClonality multiplex NGS assays; second, a standardised human cell line-based DNA control is spiked into each patient DNA sample to work as a central in-tube QC and calibrator for MRD quantification (cIT-QC). Having integrated those two reference standards in the ARResT/Interrogate bioinformatic platform, EuroClonality-NGS provides a complete protocol for standardised IG/TR gene rearrangement analysis by NGS with high reproducibility, accuracy and precision for valid marker identification and quantification in diagnostics of lymphoid malignancies.

Copy number variation: A prognostic marker for young patients with squamous cell carcinoma of the oral tongue.

BACKGROUND: The incidence of squamous cell carcinoma of the oral tongue (SCCOT) is increasing in people under age 40. There is an urgent need to identify prognostic markers that help identify young SCCOT patients with poor prognosis in order to select these for individualized treatment. MATERIALS AND METHODS: To identify genetic markers that can serve as prognostic markers for young SCCOT patients, we first investigated four young (≤40 years) and five elderly patients (≥50 years) using global RNA sequencing and whole-exome sequencing. Next, we combined our data with data on SCCOT from the cancer genome atlas (TCGA), giving a total of 16 young and 104 elderly, to explore the correlations between genomic variations and clinical outcomes. RESULTS: In agreement with previous studies, we found that SCCOT from young and elderly patients was transcriptomically and also genomically similar with no significant differences regarding cancer driver genes, germline predisposition genes, or the burden of somatic single nucleotide variations (SNVs). However, a disparate copy number variation (CNV) was found in young patients with distinct clinical outcome. Combined with data from TCGA, we found that the overall survival was significantly better in young patients with low-CNV (n = 5) compared to high-CNV (n = 11) burden (P = 0.044). CONCLUSIONS: Copy number variation burden is a useful single prognostic marker for SCCOT from young, but not elderly, patients. CNV burden thus holds promise to form an important contribution when selecting suitable treatment protocols for young patients with SCCOT.

GLASS: assisted and standardized assessment of gene variations from Sanger sequence trace data.

MOTIVATION: Sanger sequencing is still being employed for sequence variant detection by many laboratories, especially in a clinical setting. However, chromatogram interpretation often requires manual inspection and in some cases, considerable expertise. RESULTS: We present GLASS, a web-based Sanger sequence trace viewer, editor, aligner and variant caller, built to assist with the assessment of variations in 'curated' or user-provided genes. Critically, it produces a standardized variant output as recommended by the Human Genome Variation Society. AVAILABILITY AND IMPLEMENTATION: GLASS is freely available at http://bat.infspire.org/genomepd/glass/ with source code at https://github.com/infspiredBAT/GLASS. CONTACT: nikos.darzentas@gmail.com or malcikova.jitka@fnbrno.cz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

High resolution IgH repertoire analysis reveals fetal liver as the likely origin of life-long, innate B lymphopoiesis in humans.

The ontogeny of the natural, public IgM repertoire remains incompletely explored. Here, high-resolution immunogenetic analysis of B cells from (unrelated) fetal, child, and adult samples, shows that although fetal liver (FL) and bone marrow (FBM) IgM repertoires are equally diversified, FL is the main source of IgM natural immunity during the 2nd trimester. Strikingly, 0.25% of all prenatal clonotypes, comprising 18.7% of the expressed repertoire, are shared with the postnatal samples, consistent with persisting fetal IgM+ B cells being a source of natural IgM repertoire in adult life. Further, the origins of specific stereotypic IgM+ B cell receptors associated with chronic lymphocytic leukemia, can be traced back to fetal B cell lymphopoiesis, suggesting that persisting fetal B cells can be subject to malignant transformation late in life. Overall, these novel data provide unique insights into the ontogeny of physiological and malignant B lymphopoiesis that spans the human lifetime.

ARResT/Interrogate: an interactive immunoprofiler for IG/TR NGS data.

Motivation: The study of immunoglobulins and T cell receptors using next-generation sequencing has finally allowed exploring immune repertoires and responses in their immense variability and complexity. Unsurprisingly, their analysis and interpretation is a highly convoluted task. Results: We thus implemented ARResT/Interrogate, a web-based, interactive application. It can organize and filter large amounts of immunogenetic data by numerous criteria, calculate several relevant statistics, and present results in the form of multiple interconnected visualizations. Availability and Implementation: ARResT/Interrogate is implemented primarily in R, and is freely available at http://bat.infspire.org/arrest/interrogate/ Contact: nikos.darzentas@gmail.com Supplementary Information: Supplementary data are available at Bioinformatics online.

Hammock: a hidden Markov model-based peptide clustering algorithm to identify protein-interaction consensus motifs in large datasets.

MOTIVATION: Proteins often recognize their interaction partners on the basis of short linear motifs located in disordered regions on proteins' surface. Experimental techniques that study such motifs use short peptides to mimic the structural properties of interacting proteins. Continued development of these methods allows for large-scale screening, resulting in vast amounts of peptide sequences, potentially containing information on multiple protein-protein interactions. Processing of such datasets is a complex but essential task for large-scale studies investigating protein-protein interactions. RESULTS: The software tool presented in this article is able to rapidly identify multiple clusters of sequences carrying shared specificity motifs in massive datasets from various sources and generate multiple sequence alignments of identified clusters. The method was applied on a previously published smaller dataset containing distinct classes of ligands for SH3 domains, as well as on a new, an order of magnitude larger dataset containing epitopes for several monoclonal antibodies. The software successfully identified clusters of sequences mimicking epitopes of antibody targets, as well as secondary clusters revealing that the antibodies accept some deviations from original epitope sequences. Another test indicates that processing of even much larger datasets is computationally feasible. AVAILABILITY AND IMPLEMENTATION: Hammock is published under GNU GPL v. 3 license and is freely available as a standalone program (from http://www.recamo.cz/en/software/hammock-cluster-peptides/) or as a tool for the Galaxy toolbox (from https://toolshed.g2.bx.psu.edu/view/hammock/hammock). The source code can be downloaded from https://github.com/hammock-dev/hammock/releases. CONTACT: muller@mou.cz SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Discovery of a novel ligand that modulates the protein-protein interactions of the AAA+ superfamily oncoprotein reptin.

Developing approaches to discover protein-protein interactions (PPIs) remains a fundamental challenge. A chemical biology platform is applied here to identify novel PPIs for the AAA+ superfamily oncoprotein reptin. An in silico screen coupled with chemical optimization provided Liddean, a nucleotide-mimetic which modulates reptin's oligomerization status, protein-binding activity and global conformation. Combinatorial peptide phage library screening of Liddean-bound reptin with next generation sequencing identified interaction motifs including a novel reptin docking site on the p53 tumor suppressor protein. Proximity ligation assays demonstrated that endogenous reptin forms a predominantly cytoplasmic complex with its paralog pontin in cancer cells and Liddean promotes a shift of this complex to the nucleus. An emerging view of PPIs in higher eukaryotes is that they occur through a striking diversity of linear peptide motifs. The discovery of a compound that alters reptin's protein interaction landscape potentially leads to novel avenues for therapeutic development.

On parameter synthesis by parallel model checking.

An important problem in current computational systems biology is to analyze models of biological systems dynamics under parameter uncertainty. This paper presents a novel algorithm for parameter synthesis based on parallel model checking. The algorithm is conceptually universal with respect to the modeling approach employed. We introduce the algorithm, show its scalability, and examine its applicability on several biological models.