Single-cell Gene Expression Profiling Research Articles

Identification of porcine ileal innate lymphoid cells using single-cell RNA sequencing

Abstract Innate lymphoid cells (ILCs) are integral in maintaining intestinal defense and homeostasis, but intestinal ILCs have not been identified in pigs. Pigs are an important global food source and human biomedical model, thus identifying and characterizing porcine intestinal ILCs can have broad implications. Single-cell RNA sequencing of porcine ileal lymphocytes yielded 31,983 cells distributed across 54 clusters. Five clusters were closely related to T cell clusters yet lacked expression of the pan-T cell marker, CD3E. One cluster had high expression of genes related to type 3 immunity, including IL22, RORC, and CXCL8, indicating identification of putative ILC3s. The other four clusters expressed genes encoding for NK receptors (KLRK1, KLRC1, KLRD1) and effector molecules (CCL5, PRF1), yet they lacked expression of genes traditionally expressed by porcine NK cells (CD8A, KLRB1, HCST). Thus, we putatively identified the four clusters as ILC1s. Profiles of putative porcine ILC clusters were further compared to transcriptomic signatures of murine intestinal ILC subsets. Results indicated a relative enrichment of murine ILC3 gene signatures in the porcine ILC3 cluster, while relative enrichment of murine ILC1 gene signatures was observed for the other four clusters of porcine ILC1s. We further utilized single-cell gene expression profiles to develop a gating strategy to identify porcine intestinal ILCs as CD45+CD2+CD3ɛ−CD79α− lymphocytes at the protein level by flow cytometry. Altogether, the data allowed us to create the first transcriptomic descriptions of porcine intestinal ILCs and develop approaches to identify ILCs at the protein level, which will be applicable for future research.

Single-cell Spatial Proteomic Revelations on the Multiparametric MRI Heterogeneity of Clinically Significant Prostate Cancer.

Multiparametric MRI (mpMRI) has become an indispensable radiographic tool in diagnosing prostate cancer. However, mpMRI fails to visualize approximately 15% of clinically significant prostate cancer (csPCa). The molecular, cellular, and spatial underpinnings of such radiographic heterogeneity in csPCa are unclear. We examined tumor tissues from clinically matched patients with mpMRI-invisible and mpMRI-visible csPCa who underwent radical prostatectomy. Multiplex immunofluorescence single-cell spatial imaging and gene expression profiling were performed. Artificial intelligence-based analytic algorithms were developed to examine the tumor ecosystem and integrate with corresponding transcriptomics. More complex and compact epithelial tumor architectures were found in mpMRI-visible than in mpMRI-invisible prostate cancer tumors. In contrast, similar stromal patterns were detected between mpMRI-invisible prostate cancer and normal prostate tissues. Furthermore, quantification of immune cell composition and tumor-immune interactions demonstrated a lack of immune cell infiltration in the malignant but not in the adjacent nonmalignant tissue compartments, irrespective of mpMRI visibility. No significant difference in immune profiles was detected between mpMRI-visible and mpMRI-invisible prostate cancer within our patient cohort, whereas expression profiling identified a 24-gene stromal signature enriched in mpMRI-invisible prostate cancer. Prostate cancer with strong stromal signature exhibited a favorable survival outcome within The Cancer Genome Atlas prostate cancer cohort. Notably, five recurrences in the 8 mpMRI-visible patients with csPCa and no recurrence in the 8 clinically matched patients with mpMRI-invisible csPCa occurred during the 5-year follow-up post-prostatectomy. Our study identified distinct molecular, cellular, and structural characteristics associated with mpMRI-visible csPCa, whereas mpMRI-invisible tumors were similar to normal prostate tissue, likely contributing to mpMRI invisibility.

A tumor-promoting role for soluble T\u03b2RIII in glioblastoma

PurposeMembers of the transforming growth factor (TGF)-β superfamily play a key role in the regulation of the malignant phenotype of glioblastoma by promoting invasiveness, angiogenesis, immunosuppression, and maintaining stem cell-like properties. Betaglycan, a TGF-β coreceptor also known as TGF-β receptor III (TβRIII), interacts with members of the TGF-β superfamily and acts as membrane-associated or shed molecule. Shed, soluble TβRIII (sTβRIII) is produced upon ectodomain cleavage of the membrane-bound form. Elucidating the role of TβRIII may improve our understanding of TGF-β pathway activity in glioblastomaMethodsProtein levels of TβRIII were determined by immunohistochemical analyses and ex vivo single-cell gene expression profiling of glioblastoma tissue respectively. In vitro, TβRIII levels were assessed investigating long-term glioma cell lines (LTCs), cultured human brain-derived microvascular endothelial cells (hCMECs), glioblastoma-derived microvascular endothelial cells, and glioma-initiating cell lines (GICs). The impact of TβRIII on TGF-β signaling was investigated, and results were validated in a xenograft mouse glioma modelResultsImmunohistochemistry and ex vivo single-cell gene expression profiling of glioblastoma tissue showed that TβRIII was expressed in the tumor tissue, predominantly in the vascular compartment. We confirmed this pattern of TβRIII expression in vitro. Specifically, we detected sTβRIII in glioblastoma-derived microvascular endothelial cells. STβRIII facilitated TGF-β-induced Smad2 phosphorylation in vitro and overexpression of sTβRIII in a xenograft mouse glioma model led to increased levels of Smad2 phosphorylation, increased tumor volume, and decreased survivalConclusionsThese data shed light on the potential tumor-promoting role of extracellular shed TβRIII which may be released by glioblastoma endothelium with high sTβRIII levels.

Hematopoietic Stem Cell Heterogeneity Is Linked to the Initiation and Therapeutic Response of Myeloproliferative Neoplasms.

The implications of stem cell heterogeneity for disease pathogenesis and therapy are poorly defined. JAK2V617F+ myeloproliferative neoplasms (MPNs), harboring the same mutation in hematopoietic stem cells (HSCs), display diverse phenotypes, including polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). These chronic malignant disorders are ideal models to analyze the pathological consequences of stem cell heterogeneity. Single-cell gene expression profiling with parallel mutation detection demonstrated that the megakaryocyte (Mk)-primed HSC subpopulation expanded significantly with enhanced potential in untreated individuals with JAK2V617F+ ET, driven primarily by the JAK2 mutation and elevated interferon signaling. During treatment, mutant HSCs were targeted preferentially in the Mk-primed HSC subpopulation. Interestingly, homozygous mutant HSCs were forced to re-enter quiescence, whereas their heterozygous counterparts underwent apoptosis. This study provides important evidence for the association of stem cell heterogeneity with the pathogenesis and therapeutic response of a malignant disease.

CD81 marks immature and dedifferentiated pancreatic β-cells

ObjectiveIslets of Langerhans contain heterogeneous populations of insulin-producing β-cells. Surface markers and respective antibodies for isolation, tracking, and analysis are urgently needed to study β-cell heterogeneity and explore the mechanisms to harness the regenerative potential of immature β-cells. MethodsWe performed single-cell mRNA profiling of early postnatal mouse islets and re-analyzed several single-cell mRNA sequencing datasets from mouse and human pancreas and islets. We used mouse primary islets, iPSC-derived endocrine cells, Min6 insulinoma, and human EndoC-βH1 β-cell lines and performed FAC sorting, Western blotting, and imaging to support and complement the findings from the data analyses. ResultsWe found that all endocrine cell types expressed the cluster of differentiation 81 (CD81) during pancreas development, but the expression levels of this protein were gradually reduced in β-cells during postnatal maturation. Single-cell gene expression profiling and high-resolution imaging revealed an immature signature of β-cells expressing high levels of CD81 (CD81high) compared to a more mature population expressing no or low levels of this protein (CD81low/-). Analysis of β-cells from different diabetic mouse models and in vitro β-cell stress assays indicated an upregulation of CD81 expression levels in stressed and dedifferentiated β-cells. Similarly, CD81 was upregulated and marked stressed human β-cells in vitro. ConclusionsWe identified CD81 as a novel surface marker that labels immature, stressed, and dedifferentiated β-cells in the adult mouse and human islets. This novel surface marker will allow us to better study β-cell heterogeneity in healthy subjects and diabetes progression.

Endoglin and TGF-\u03b2 signaling in glioblastoma

Microvascular proliferation is a key feature of glioblastoma and neovascularization has been implicated in tumor progression. Glioblastomas use pro-angiogenic factors such as vascular endothelial growth factor (VEGF) for new blood vessel formation. Yet, anti-VEGF therapy does not prolong overall survival so that alternative angiogenic pathways may need to be explored as drug targets. Both glioma cells and glioma-associated endothelial cells produce TGF-β superfamily ligands which bind TGF-β receptors (TGF-βR). The TGF-βR type III endoglin (CD105), is a marker of proliferating endothelium that has already been studied as a potential therapeutic target. We studied endoglin expression in glioblastoma tissue and in glioma-associated endothelial cells in a cohort of 52 newly diagnosed and 10 recurrent glioblastoma patients by immunohistochemistry and by ex vivo single-cell gene expression profiling of 6 tumors. Endoglin protein levels were similar in tumor stroma and endothelium and correlated within tumors. Similarly, endoglin mRNA determined by ex vivo single-cell gene expression profiling was expressed in both compartments. There was positive correlation between endoglin and proteins of TGF-β superfamily signaling. No prognostic role of endoglin expression in either compartment was identified. Endoglin gene silencing in T98G glioma cells and in human cerebral microvascular endothelial cells (hCMEC) did not affect constitutive or exogenous TGF-β superfamily ligand-dependent signaling, except for a minor facilitation of pSmad1/5 signaling in hCMEC. These observations challenge the notion that endoglin might become a promising therapeutic target in glioblastoma.

A Modified SMART-Seq Method for Single-Cell Transcriptomic Analysis of Embryoid Body Differentiation.

Embryoid bodies (EBs) are aggregate of cells that contain three embryonic germ layers. They can be formed by direct differentiation from pluripotent embryonic stem cells (ESCs), which serves as a useful model for understanding early embryo development. Due to the mixture of different cell types, it is necessary to investigate EBs at the single-cell level. Here, we describe a robust and straightforward method for single-cell gene expression profiling during mouse EB differentiation from mouse ESCs (mESCs). The protocol is modified from a widely used method in the SMART-seq family, which only requires standard molecular biology techniques and lab equipment. It allows for accurate 3' counting of transcript at the single-cell level, which helps reveal cellular identities during EB formation. Combined with perturbation experiments, the method provides an opportunity for mechanistic studies of embryo development at the single-cell level.

Identification of stochastic gene expression models over lineage trees

In previous work, we have developed an autoregressive Mixed-Effects model of the evolution of the kinetic gene expression parameters along cell generations, and an identification method simultaneously exploiting single-cell gene expression profiles and known parental relationships among cells (lineage tree data). Here, we extend our modelling and identification approach to explicitly account for stochasticity of promoter activation, and demonstrate via simulation the performance of the method and the improvement relative to the original approach where this source of noise is not accounted for.

Monocyte Recruitment, Specification, and Function in Atherosclerosis.

Atherosclerotic lesions progress through the continued recruitment of circulating blood monocytes that differentiate into macrophages within plaque. Lesion-associated macrophages are the primary immune cells present in plaque, where they take up cholesterol and store lipids in the form of small droplets resulting in a unique morphology termed foam cell. Recent scientific advances have used single-cell gene expression profiling, live-cell imaging, and fate mapping approaches to describe macrophage and monocyte contributions to pro- or anti-inflammatory mechanisms, in addition to functions of motility and proliferation within lesions. Yet, many questions regarding tissue-specific regulation of monocyte-to-macrophage differentiation and the contribution of recruited monocytes at stages of atherosclerotic disease progression remain unknown. In this review, we highlight recent advances regarding the role of monocyte and macrophage dynamics in atherosclerotic disease and identify gaps in knowledge that we hope will allow for advancing therapeutic treatment or prevention strategies for cardiovascular disease.

A Progressive Somatic Cell Niche Regulates Germline Cyst Differentiation in the Drosophila Ovary

In the germarium of the Drosophila ovary, developing germline cysts are surrounded by a population of somatic escort cells that are known to function as the niche cells for germline differentiation;1 however, the underlying molecular mechanisms of this niche function remain poorly understood. Through single-cell gene expression profiling combined with genetic analyses, we here demonstrate that the escort cells can be spatially and functionally divided into two successive domains. The anterior escort cells (aECs) specifically produce ecdysone, which acts on the cystoblast to promote synchronous cell division, whereas the posterior escort cells (pECs) respond to ecdysone signaling and regulate soma-germline cell adhesion to promote the transition from 16-cell cyst-to-egg chamber formation. The patterning of the aEC and pEC domains is independent of the germline but is dependent on JAK/STAT signaling activity, which emanates from the posterior. Thus, a heterogeneous population of escort cells constitutes a stepwise niche environment to orchestrate cystoblast division and differentiation toward egg chamber formation.

T Follicular Regulatory Cell-Derived Fibrinogen-like Protein 2 Regulates Production of Autoantibodies and Induction of Systemic Autoimmunity.

T follicular regulatory (TFR) cells limit Ab responses, but the underlying mechanisms remain largely unknown. In this study, we identify Fgl2 as a soluble TFR cell effector molecule through single-cell gene expression profiling. Highly expressed by TFR cells, Fgl2 directly binds to B cells, especially light-zone germinal center B cells, as well as to T follicular helper (TFH) cells, and directly regulates B cells and TFH in a context-dependent and type 2 Ab isotype-specific manner. In TFH cells, Fgl2 induces the expression of Prdm1 and a panel of checkpoint molecules, including PD1, TIM3, LAG3, and TIGIT, resulting in TFH cell dysfunction. Mice deficient in Fgl2 had dysregulated Ab responses at steady-state and upon immunization. In addition, loss of Fgl2 results in expansion of autoreactive B cells upon immunization. Consistent with this observation, aged Fgl2-/- mice spontaneously developed autoimmunity associated with elevated autoantibodies. Thus, Fgl2 is a TFR cell effector molecule that regulates humoral immunity and limits systemic autoimmunity.

Uncovering the genetic blueprint of the C. elegans nervous system

Despite rapid advances in connectome mapping and neuronal genetics, we lack theoretical and computational tools to unveil, in an experimentally testable fashion, the genetic mechanisms that govern neuronal wiring. Here we introduce a computational framework to link the adjacency matrix of a connectome to the expression patterns of its neurons, helping us uncover a set of genetic rules that govern the interactions between neurons in contact. The method incorporates the biological realities of the system, accounting for noise from data collection limitations, as well as spatial restrictions. The resulting methodology allows us to infer a network of 19 innexin interactions that govern the formation of gap junctions in Caenorhabditis elegans, five of which are already supported by experimental data. As advances in single-cell gene expression profiling increase the accuracy and the coverage of the data, the developed framework will allow researchers to systematically infer experimentally testable connection rules, offering mechanistic predictions for synapse and gap junction formation.

Abstract PO-010: Elucidating intratumoral heterogeneity and predicting effective combination regimens in PDAC PDOs using scRNA-seq and snATAC-seq

Abstract Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related death in the United States. The overwhelming majority of patients (up to 85%) present with unresectable disease, and the 5-year survival rate stands at a dire 9%. Current chemotherapeutic regimens extend survival by only a few months, and the molecular underpinnings of treatment failure in advanced disease remain largely unknown. Recently, single-cell sequencing techniques have emerged as highly effective methods to uncover intratumoral heterogeneity across many cancer types, including PDAC. These studies, and our own unpublished data, have reiterated profound transcriptomic subclonal diversity in PDAC, which likely underlies the divergent therapeutic responses and eventual treatment failure. Using a patient-derived organoid (PDO) platform, we have characterized, on the single cell level, gene expression and regulation profiles to understand the heterogeneity and clinical utility of this model. We applied predictive RNA-seq-based algorithms (CMap) to our initial PDO profiling data to design “custom” PDO combinatorial regimens as a true precision medicine-based approach. We are in the process of validating these predictions in vitro; however, preliminary single-cell RNA (scRNA-seq) data shows treatment PDOs with CMap-predicted compounds induced dramatic transcriptomic shifts in subclones reflective of an efficacious treatment strategy. Additionally, we conducted single-nuclei ATAC sequencing (snATAC-seq) of PDOs pre- and post-treatment with CMap-predicted compounds. This data, coupled to our scRNA-seq, allowed for construction of chromatin regulatory maps, and determined alterations in chromatin accessibility and gene regulation induced by targeted combinatorial therapeutics. These findings provide meaningful insight to biological processes driven by treatment-induced chromatin accessibility, and its relationship to heterogeneous transcriptional architecture. Our data suggests that differential regulation across PDO subclones may drive responses to therapy and acquired resistance mechanisms observed in the clinic, which could be predicted and therapeutically targeted with scRNA sequencing. Thus, this work represents the importance of leveraging subclonal architecture in the preclinical space to ensure both treatment efficacy and the consideration of novel therapeutic combinations in PDAC patients. Citation Format: Paola A. Guerrero, Anirban Maitra, Maria E. Monberg, Jaewon J Lee, Vincent Bernard-Pagan, Senthil Muthuswamy. Elucidating intratumoral heterogeneity and predicting effective combination regimens in PDAC PDOs using scRNA-seq and snATAC-seq [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PO-010.

EPCO-37. USING SINGLE-CELL RNA SEQUENCING TO IDENTIFY CELLULAR HETEROGENEITY WITHIN NON-FUNCTIONING PITUITARY ADENOMAS

Abstract Pituitary adenomas (PA) are one of the most common primary brain tumors and comprise approximately 15% of brain neoplasms. Most PA are histologically benign but can cause significant morbidity. Previous studies utilized whole-genome and exome sequencing to identify a few somatic variants, but no recurrent mutations were observed. Further studies are warranted to identify driver mutations occurring at low frequencies. We used single-cell RNA sequencing (10X Genomics) to investigate cellular heterogeneity in three non-functioning pituitary adenomas. Our analysis identified discrete clusters of cells associated with specific functional pathways. One of these clusters corresponded to cells expressing genes related to metabolic pathways, primarily lipid metabolism. Another cluster consistent amongst the three patients comprised of cells involved in antigen presentation and processing. In addition, the copy number variation analysis highlighted distinct chromosomal alterations within our samples. Interestingly, we were able to identify clonal variations within each tumor based on chromosomal aberrations. For example, in our first patient, we observed a gain of chromosome 19 and loss of chromosome 2. Our analysis showed three different clonal populations within this tumor. All three populations harbored the loss of chromosome 2, one population exhibited gain of chromosome 19, while a third population exhibited loss of chromosome 19. These early results indicate the loss of chromosome 2 as an early event in tumorigenesis and gain/loss of chromosome 19 as late events. We are currently in a process of identifying somatic variations within these tumors by variant calling. Currently we are expanding our analysis to 20 non-functional PA. Mapping the single-cell gene expression profiles with mutational phylogeny will reveal the differences in clonal evolution within the tumor subtypes. This study will help us define the molecular fingerprint of pituitary adenomas and provide insights which could be utilized in the clinic for better management of these tumors.

Iron Trafficking through Macrophages Regulates Signaling Pathways in Myeloma

Background Iron is an essential element for cell growth, including cancer cells, and is present in the microenvironment. We have shown that multiple myeloma (MM) cells have abnormal iron metabolism and harbor increased intracellular iron. However, the mechanism by which MM cells retain iron has remained largely elusive. Methods Expression and clinical relevance of the transferrin receptor in MM samples were analyzed in publicly available microarray and RNA-sequencing databases. Macrophages were isolated from C57BL/6J mice and were induced to specific subtypes by cytokines or culturing with MM cells. The 5TGM1-KaLwRij MM mice were used to confirm whether MM cells induce macrophage polarization in vivo. Specific subtypes of macrophage and transferrin receptor expression in MM cells were assessed by flow cytometry. Expression of ferroportin (FPN1) and ferritin in MM cells and/or macrophages were analyzed by Western blots. Single-cell RNA-sequencing (scRNA-seq), RNA-seq, and gene expression profiles (GEPs) were employed to identify ferroportin-signaling pathways in both tumor cells and macrophages of primary human MM samples. Results MM cells induced polarization with a significant increase of CD38+CD206- M1 macrophages both in vitro and in vivo. We also confirmed that the tumor associated macrophages (TAMs) were increased in the 5TGM1-KaLwRij MM mice. MM cells upregulated ferroportin expression in macrophages to provide iron to MM cells in co-culture studies and in vivo models. The transferrin receptor antibody treatment prevented MM cells from taking up iron from macrophages. scRNA-seq identified a subset of FPN1+ TAMs in human bone marrow aspirates, which are assumed to provide iron to MM cells. Using RNA-seq and GEPs analyses in primary human samples, multiple signaling pathways were differentially modulated in FPN1+ versus FPN1- TAMs, including those related to inflammation and apoptosis Conclusions Increased expression of the transferrin receptor in MM cells strongly suggests that tumor cells take up iron from its environment. MM cells promote intracellular iron mobilization in macrophages, which provide iron to MM cells in a transferrin-dependent manner. Blockade of iron trafficking between MM cells and macrophages might be a promising approach to MM therapy. Disclosures van Rhee: EUSA: Consultancy; CDCN: Consultancy; Karyopharm: Consultancy; Adaptive Biotech: Consultancy; Takeda: Consultancy.

Abstract PO-015: Ex-vivo stimulation of chimeric antigen receptor T cell pre-infusion products predicts clinical response in pediatric B cell acute lymphoblastic leukemia

Abstract CAR T cell therapy has shown remarkable efficacy against refractory hematological malignancies, frequently leading to complete remission. However, some patients do not respond to the therapy, and many patients who do show an initial response eventually relapse. The factors determining these diverse patient responses remain to be understood. We sought to assess whether the intrinsic molecular characteristics of CAR T pre-infusion products could be predictive of clinical outcomes, reasoning that differences in T cell cellular states and subtype proportions determine response. To investigate the heterogeneity and temporal dynamics of CD19-targeted CAR T cells at a molecular level and the relationship to clinical variables in pediatric B cell acute lymphoblastic leukemia, we profiled by single-cell RNA-seq patient-derived pre-infusion CAR T cells before and after stimulation ex-vivo by antigen presenting cells. Computational analysis of data from 12 pediatric patients with chemotherapy-resistant or refractory disease revealed distinct populations of T cells associated with clinical response. We found that CAR T cells from patients with a favorable response had an increased potential to transition to an active, cytokine-expressing state upon stimulation with CD19, and that responding patients were particularly associated with a robust mixed CD4/CD8 Type 1 helper-like response. Conversely, we found that patients who do not did not respond to CAR T therapy had a higher proportion of non-cytokine expressing CD8 cytotoxic T cells upon stimulation. These results demonstrate the potential of single-cell gene expression profiling coupled with computational analysis to uncover the molecular factors determining response to immunotherapy. Citation Format: Steven Woodhouse, Zhiliang Bai, Rong Fan, Pablo G. Camara, J. Joseph Melenhorst. Ex-vivo stimulation of chimeric antigen receptor T cell pre-infusion products predicts clinical response in pediatric B cell acute lymphoblastic leukemia [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-015.

Predicting single-cell gene expression profiles of imaging flow cytometry data with machine learning.

High-content imaging and single-cell genomics are two of the most prominent high-throughput technologies for studying cellular properties and functions at scale. Recent studies have demonstrated that information in large imaging datasets can be used to estimate gene mutations and to predict the cell-cycle state and the cellular decision making directly from cellular morphology. Thus, high-throughput imaging methodologies, such as imaging flow cytometry can potentially aim beyond simple sorting of cell-populations. We introduce IFC-seq, a machine learning methodology for predicting the expression profile of every cell in an imaging flow cytometry experiment. Since it is to-date unfeasible to observe single-cell gene expression and morphology in flow, we integrate uncoupled imaging data with an independent transcriptomics dataset by leveraging common surface markers. We demonstrate that IFC-seq successfully models gene expression of a moderate number of key gene-markers for two independent imaging flow cytometry datasets: (i) human blood mononuclear cells and (ii) mouse myeloid progenitor cells. In the case of mouse myeloid progenitor cells IFC-seq can predict gene expression directly from brightfield images in a label-free manner, using a convolutional neural network. The proposed method promises to add gene expression information to existing and new imaging flow cytometry datasets, at no additional cost.

A Highly Scalable Method for Joint Whole-Genome Sequencing and Gene-Expression Profiling of Single Cells

To address how genetic variation alters gene expression in complex cell mixtures, we developed direct nuclear tagmentation and RNA sequencing (DNTR-seq), which enables whole-genome and mRNA sequencing jointly in single cells. DNTR-seq readily identified minor subclones within leukemia patients. In a large-scale DNA damage screen, DNTR-seq was used to detect regions under purifying selection and identified genes where mRNA abundance was resistant to copy-number alteration, suggesting strong genetic compensation. mRNA sequencing (mRNA-seq) quality equals RNA-only methods, and the low positional bias of genomic libraries allowed detection of sub-megabase aberrations at ultra-low coverage. Each cell library is individually addressable and can be re-sequenced at increased depth, allowing multi-tiered study designs. Additionally, the direct tagmentation protocol enables coverage-independent estimation of ploidy, which can be used to identify cell singlets. Thus, DNTR-seq directly links each cell's state to its corresponding genome at scale, enabling routine analysis of heterogeneous tumors and other complex tissues.

STAB: a spatio-temporal cell atlas of the human brain.

The human brain is the most complex organ consisting of billions of neuronal and non-neuronal cells that are organized into distinct anatomical and functional regions. Elucidating the cellular and transcriptome architecture underlying the brain is crucial for understanding brain functions and brain disorders. Thanks to the single-cell RNA sequencing technologies, it is becoming possible to dissect the cellular compositions of the brain. Although great effort has been made to explore the transcriptome architecture of the human brain, a comprehensive database with dynamic cellular compositions and molecular characteristics of the human brain during the lifespan is still not available. Here, we present STAB (a Spatio-Temporal cell Atlas of the human Brain), a database consists of single-cell transcriptomes across multiple brain regions and developmental periods. Right now, STAB contains single-cell gene expression profiling of 42 cell subtypes across 20 brain regions and 11 developmental periods. With STAB, the landscape of cell types and their regional heterogeneity and temporal dynamics across the human brain can be clearly seen, which can help to understand both the development of the normal human brain and the etiology of neuropsychiatric disorders. STAB is available at http://stab.comp-sysbio.org.

Abstract 2757: Analysis of stromal myofibroblasts identifies secreted proteins that promote pancreatic ductal adenocarcinoma

Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of the most incurable types of cancer. Cancer that develops in the acinar cells of the pancreas is typically not diagnosed until later stages, such as stage 3 or 4. As such, this form of cancer is particularly lethal with only 9% of patients reaching 5-year survival. PDAC is known to have a particularly dense extracellular matrix composed of fibroblasts, which have been previously shown to play an important role in promoting resistance to drug therapy. Characterization of the stromal networks involved in PDAC tumor development as well as protein markers of fibroblast subpopulations within the tumor stroma are critical to developing new fibroblast-targeted therapeutic approaches as well as understanding key signaling molecules that ultimately promote tumor progression and drug resistance. Single-cell RNA sequencing (scRNAseq) was utilized to analyze cancer-associated fibroblasts (CAFs) from KPC mouse-derived, MT3 subcutaneous murine allografts along with two fibroblast lines derived from human PDAC tumors: CRC-811 and IA-1340. Single cell gene expression profiling and subsequent analysis of MT3-derived CAFs resulted in the identification of three CAF subpopulations including a myofibroblast subpopulation that expressed high levels of smooth muscle actin (Acta2), which was also observed in both human samples. Fibroblast subpopulations enriched in Acta2 expression, expressed high levels of Wnt5a along with several other secreted factors including Tgfb1, Tgfb2 and Ctgf. Wnt5a is a secreted protein that activates non-canonical Wnt signaling pathways and is known to regulate normal developmental processes, including proliferation, differentiation, migration, adhesion and polarity. However Wnt5a is not natively expressed in MT3 cancer cells derived from syngeneic tumors, but potentially in the stroma. We hypothesize it is exclusively derived from fibroblasts. Previously it has been shown that Wnt5a inhibition suppressed gastric cancer metastasis, therefore further validation of the role of myofibroblast-derived Wnt5a on PDAC disease progression is warranted. This study received funding by LDRD 19-SI-003. This work was conducted under the auspices of the USDOE by LLNL (DE-AC52-07NA27344). IM Release Number: LLNL-ABS-798442. Citation Format: Kelly A. Martin, Aimy Sebastian, Nicholas R. Hum, Stephen Byers, Elizabeth K. Wheeler, Matthew A. Coleman, Gabriela G. Loots. Analysis of stromal myofibroblasts identifies secreted proteins that promote pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2757.