Using adjusted local assortativity with Molecular Pixelation unveils colocalization of membrane proteins with immunological significance.

Advances in spatial proteomics and protein colocalization are a driving force in the understanding of cellular mechanisms and their influence on biological processes. New methods in the field of spatial proteomics call for the development of algorithms and open up new avenues of research. The newly introduced Molecular Pixelation (MPX) provides spatial information on surface proteins and their relationship with each other in single cells. This allows for in silico representation of neighborhoods of membrane proteins as graphs. In order to analyze this new data modality, we adapted local assortativity in networks of MPX single-cell graphs and created a method that is able to capture detailed information on the spatial relationships of proteins. The introduced method can evaluate the pairwise colocalization of proteins and access higher-order similarity to investigate the colocalization of multiple proteins at the same time. We evaluated the method using publicly available MPX datasets where T cells were treated with a chemokine to study uropod formation. We demonstrate that adjusted local assortativity detects the effects of the stimuli at both single- and multiple-marker levels, which enhances our understanding of the uropod formation. We also applied our method to treating cancerous B-cell lines using a therapeutic antibody. With the adjusted local assortativity, we recapitulated the effect of rituximab on the polarity of CD20. Our computational method together with MPX improves our understanding of not only the formation of cell polarity and protein colocalization under stimuli but also advancing the overall insight into immune reaction and reorganization of cell surface proteins, which in turn allows the design of novel therapies. We foresee its applicability to other types of biological spatial data when represented as undirected graphs.

Molecular pixelation: spatial proteomics of single cells by sequencing.

The spatial distribution of cell surface proteins governs vital processes of the immune system such as intercellular communication and mobility. However, fluorescence microscopy has limited scalability in the multiplexing and throughput needed to drive spatial proteomics discoveries at subcellular level. We present Molecular Pixelation (MPX), an optics-free, DNA sequence-based method for spatial proteomics of single cells using antibody-oligonucleotide conjugates (AOCs) and DNA-based, nanometer-sized molecular pixels. The relative locations of AOCs are inferred by sequentially associating them into local neighborhoods using the sequence-unique DNA pixels, forming >1,000 spatially connected zones per cell in 3D. For each single cell, DNA-sequencing reads are computationally arranged into spatial proteomics networks for 76 proteins. By studying immune cell dynamics using spatial statistics on graph representations of the data, we identify known and new patterns of spatial organization of proteins on chemokine-stimulated T cells, highlighting the potential of MPX in defining cell states by the spatial arrangement of proteins.

GPSeq reveals the radial organization of chromatin in the cell nucleus.

With the exception of lamina-associated domains, the radial organization of chromatin in mammalian cells remains largely unexplored. Here we describe genomic loci positioning by sequencing (GPSeq), a genome-wide method for inferring distances to the nuclear lamina all along the nuclear radius. GPSeq relies on gradual restriction digestion of chromatin from the nuclear lamina toward the nucleus center, followed by sequencing of the generated cut sites. Using GPSeq, we mapped the radial organization of the human genome at 100-kb resolution, which revealed radial patterns of genomic and epigenomic features and gene expression, as well as A and B subcompartments. By combining radial information with chromosome contact frequencies measured by Hi-C, we substantially improved the accuracy of whole-genome structure modeling. Finally, we charted the radial topography of DNA double-strand breaks, germline variants and cancer mutations and found that they have distinctive radial arrangements in A and B subcompartments. We conclude that GPSeq can reveal fundamental aspects of genome architecture.

Interferon γ is a strong, STAT1-dependent direct inducer of BCL6 expression in multiple myeloma cells.

B-cell CLL/lymphoma 6 (BCL6) is a transcriptional master regulator that can repress more than 1200 potential target genes. It exerts oncogenic effects through the inhibition of differentiation, DNA damage sensing and apoptosis in several human hematopoietic malignancies, including multiple myeloma (MM). The multifunctional cytokine interferon γ (IFNγ) exerts pro-apoptotic and anti-proliferative effects on MM cells in vitro, at least partially through the inhibition of the effects of interleukin 6 (IL6), one of the most important growth factor of MM and a strong inducer of BCL6 expression. However, IFNγ was also reported to directly upregulate BCL6 in several cell types. These observations prompted us to analyze the effect of IFNγ on BCL6 expression in MM cells. We discovered that among several myeloma growth/survival factors tested (including IL6, oncostatin M, insulin-like growth factor 1, tumor necrosis factor α and IFNα) IFNγ was the strongest inducer of BCL6 mRNA and protein expression in MM cell lines. IFNγ induced upregulation of BCL6 was dependent on the classical STAT1 signaling pathway, and affected both major BCL6 variants. Interestingly, although IFNα induced stronger STAT1 phosphorylation than IFNγ, it only slightly upregulated BCL6 in MM lines. We proved that IFNα induced BCL6 upregulation was limited by the concomitant activation of STAT5 signaling. We assume that BCL6 upregulation may represent a potentially pro-tumorigenic effect of IFNγ signaling in MM cells.

Genome-Wide Profiling of DNA Double-Strand Breaks by the BLESS and BLISS Methods.

DNA double-strand breaks (DSBs) are major DNA lesions that are constantly formed during physiological processes such as DNA replication, transcription, and recombination, or as a result of exogenous agents such as ionizing radiation, radiomimetic drugs, and genome editing nucleases. Unrepaired DSBs threaten genomic stability by leading to the formation of potentially oncogenic rearrangements such as translocations. In past few years, several methods based on next-generation sequencing (NGS) have been developed to study the genome-wide distribution of DSBs or their conversion to translocation events. We developed Breaks Labeling, Enrichment on Streptavidin, and Sequencing (BLESS), which was the first method for direct labeling of DSBs in situ followed by their genome-wide mapping at nucleotide resolution (Crosetto et al., Nat Methods 10:361-365, 2013). Recently, we have further expanded the quantitative nature, applicability, and scalability of BLESS by developing Breaks Labeling In Situ and Sequencing (BLISS) (Yan et al., Nat Commun 8:15058, 2017). Here, we first present an overview of existing methods for genome-wide localization of DSBs, and then focus on the BLESS and BLISS methods, discussing different assay design options depending on the sample type and application.

BLISS is a versatile and quantitative method for genome-wide profiling of DNA double-strand breaks.

Precisely measuring the location and frequency of DNA double-strand breaks (DSBs) along the genome is instrumental to understanding genomic fragility, but current methods are limited in versatility, sensitivity or practicality. Here we present Breaks Labeling In Situ and Sequencing (BLISS), featuring the following: (1) direct labelling of DSBs in fixed cells or tissue sections on a solid surface; (2) low-input requirement by linear amplification of tagged DSBs by in vitro transcription; (3) quantification of DSBs through unique molecular identifiers; and (4) easy scalability and multiplexing. We apply BLISS to profile endogenous and exogenous DSBs in low-input samples of cancer cells, embryonic stem cells and liver tissue. We demonstrate the sensitivity of BLISS by assessing the genome-wide off-target activity of two CRISPR-associated RNA-guided endonucleases, Cas9 and Cpf1, observing that Cpf1 has higher specificity than Cas9. Our results establish BLISS as a versatile, sensitive and efficient method for genome-wide DSB mapping in many applications.