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Open Access Publications from the University of California

Scholarly Works (58 results)

  • Thesis
  • Peer Reviewed
UCLA Electronic Theses and Dissertations (2020)

3’ RNA sequencing provides an alternative to whole transcript analysis. However, we do not know a priori the relative advantage of each method. Thus, a comprehensive comparison between the whole transcript and the 3’ method is needed to determine their relative merits. Single cell RNA sequencing (scRNA-seq) enables the profiling of the transcriptomes of individual cells. Cell type identification is one of the major goals in scRNA-seq. Current methods for assigning cell types have several limitations, such as unwanted sources of variation that influence clustering and a lack of canonical markers for certain cell types. Thus, new methods need to be developed. We first used two commercially available library preparation kits, the KAPA Stranded mRNA-seq kit (traditional method) and the Lexogen QuantSeq 3’ mRNA-seq kit (3’ method), to determine the advantages and disadvantages of these two approaches. We found that the 3’ RNA-seq method detected more short transcripts than the whole transcript method. With regard to differential expression analysis, we found that the whole transcript method detected more differentially expressed genes, regardless of the level of sequencing depth. We then developed ACTINN (Automated Cell Type Identification using Neural Networks), which employs a neural network to predicts cell types for scRNA-seq datasets. We trained and tested ACTINN on multiple datasets, the results showed that ACTINN is fast and accurate, and should therefore be a useful tool to complement existing scRNA-seq pipelines. Lastly, we performed scRNA-seq to study gene networks associated with host defense comparing lesions from reversal reaction vs. lepromatous lesions from leprosy patients. We constructed an antimicrobial ecosystem by integrating the IFNG and IL1B antimicrobial targets with the cell-cell co-abundance in lesions, which revealed that the interaction of dendritic cells, macrophages, T cells, keratinocytes and fibroblasts contributes to the capacity of granulomas to eliminate the pathogen in leprosy.

    Cover page: Methods for the Analysis and Interpretation of Single Cell RNA Sequencing Data
    • Article
    • Peer Reviewed
    UC Berkeley Previously Published Works (2021)
    The photosynthetic unicellular alga Chlamydomonas (Chlamydomonas reinhardtii) is a versatile reference for algal biology because of its ease of culture in the laboratory. Genomic and systems biology approaches have previously described transcriptome responses to environmental changes using bulk data, thus representing the average behavior from pools of cells. Here, we apply single-cell RNA sequencing (scRNA-seq) to probe the heterogeneity of Chlamydomonas cell populations under three environments and in two genotypes differing by the presence of a cell wall. First, we determined that RNA can be extracted from single algal cells with or without a cell wall, offering the possibility to sample natural algal communities. Second, scRNA-seq successfully separated single cells into nonoverlapping cell clusters according to their growth conditions. Cells exposed to iron or nitrogen deficiency were easily distinguished despite a shared tendency to arrest photosynthesis and cell division to economize resources. Notably, these groups of cells not only recapitulated known patterns observed with bulk RNA-seq but also revealed their inherent heterogeneity. A substantial source of variation between cells originated from their endogenous diurnal phase, although cultures were grown in constant light. We exploited this result to show that circadian iron responses may be conserved from algae to land plants. We document experimentally that bulk RNA-seq data represent an average of typically hidden heterogeneity in the population.
      Cover page: Single-cell RNA sequencing of batch Chlamydomonas cultures reveals heterogeneity in their diurnal cycle phase
      • Article
      • Peer Reviewed
      UCLA Previously Published Works (2020)
      Cardiac fibrosis is a pathophysiologic hallmark of the aging heart, but little is known about how fibroblast proliferation and transcriptional programs change throughout the life span of the organism. Using EdU pulse labeling, we demonstrated that more than 50% of cardiac fibroblasts were actively proliferating in the first day of postnatal life. However, by 4 weeks, only 10% of cardiac fibroblasts were proliferating. By early adulthood, the fraction of proliferating cardiac fibroblasts further decreased to approximately 2%, where it remained throughout the rest of the organism's life. We observed that maximal changes in cardiac fibroblast transcriptional programs and, in particular, collagen and ECM gene expression both in the heart and cardiac fibroblast were maximal in the newly born and juvenile animal and decreased with organismal aging. Examination of DNA methylation changes both in the heart and in cardiac fibroblasts did not demonstrate significant changes in differentially methylated regions between young and old mice. Our observations demonstrate that cardiac fibroblasts attain a stable proliferation rate and transcriptional program early in the life span of the organism and suggest that phenotypic changes in the aging heart are not directly attributable to changes in proliferation rate or altered collagen expression in cardiac fibroblasts.
        Cover page: Cardiac fibroblast proliferation rates and collagen expression mature early and are unaltered with advancing age
        • Article
        • Peer Reviewed
        UCLA Previously Published Works (2022)
        Natural killer (NK) cells are innate lymphocytes that possess traits of adaptive immunity, such as memory formation. However, the molecular mechanisms by which NK cells persist to form memory cells are not well understood. Using single-cell RNA sequencing, we identified two distinct effector NK cell (NKeff) populations following mouse cytomegalovirus infection. Ly6C- memory precursor (MP) NK cells showed enhanced survival during the contraction phase in a Bcl2-dependent manner, and differentiated into Ly6C+ memory NK cells. MP NK cells exhibited distinct transcriptional and epigenetic signatures compared with Ly6C+ NKeff cells, with a core epigenetic signature shared with MP CD8+ T cells enriched in ETS1 and Fli1 DNA-binding motifs. Fli1 was induced by STAT5 signaling ex vivo, and increased levels of the pro-apoptotic factor Bim in early effector NK cells following viral infection. These results suggest that a NK cell-intrinsic checkpoint controlled by the transcription factor Fli1 limits MP NK formation by regulating early effector NK cell fitness during viral infection.
          Cover page: The transcription factor Fli1 restricts the formation of memory precursor NK cells during viral infection
          • Article
          • Peer Reviewed
          UCLA Previously Published Works (2021)
          White adipose tissue (WAT) is an essential regulator of energy storage and systemic metabolic homeostasis. Regulatory networks consisting of immune and structural cells are necessary to maintain WAT metabolism, which can become impaired during obesity in mammals. Using single-cell transcriptomics and flow cytometry, we unveil a large-scale comprehensive cellular census of the stromal vascular fraction of healthy lean and obese human WAT. We report new subsets and developmental trajectories of adipose-resident innate lymphoid cells, dendritic cells and monocyte-derived macrophage populations that accumulate in obese WAT. Analysis of cell-cell ligand-receptor interactions and obesity-enriched signaling pathways revealed a switch from immunoregulatory mechanisms in lean WAT to inflammatory networks in obese WAT. These results provide a detailed and unbiased cellular landscape of homeostatic and inflammatory circuits in healthy human WAT.
            Cover page: Single-cell sequencing of human white adipose tissue identifies new cell states in health and obesity
            • Article
            • Peer Reviewed
            UCLA Previously Published Works (2020)
            BACKGROUND/AIM:This study aimed to measure the DNA methylation state of thousands of CpG islands in the blood of two monozygotic twins that were discordant for cardiovascular disease (CVD). Twin 1 had suffered myocardial infarction, while the other was healthy. PATIENTS AND METHODS:Since the aim of this study was to identify differentially methylated regions which might act as potential markers, reduced-representation bisulfite libraries were used for whole-genome methylation analysis. RESULTS:According to the analysis, 11 genes lipid droplet associated hydrolase (LDAH), apolipoprotein B (APOB), acyl-CoA synthetase medium chain family member 2A (ACSM2A), acyl-CoA synthetase medium chain family member 5(ACSM5), acyl-CoA synthetase family member 3 (ACSF3), carboxylesterase 1 (CES1), carboxylesterase 1 pseudogene 1 (CES1P1), AFG3 like matrix AAA peptidase subunit 2 (AFG3L2), iron-sulfur cluster assembly enzyme (ISCU), SEC14 like lipid binding 2 (SEC14L2) and microsomal triglyceride transfer protein (MTTP) were all hypomethylated in DNA from twin 2, the unaffected twin. Methylation changes were observed at different multiple loci between the twins, suggesting loci that are affected by disease status in identical genetic backgrounds. CONCLUSION:This twin study may contribute significantly to the understanding of the genetic basis of CVD and resulting myocardial infarction. This approach may allow identification of possible target loci associated with aberrant epigenetic regulation in CVD.
              Cover page: Genome-wide DNA Methylation Profiling of Blood from Monozygotic Twins Discordant for Myocardial Infarction
              • Article
              • Peer Reviewed
              UCLA Previously Published Works (2019)
              Whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) are widely used for measuring DNA methylation levels on a genome-wide scale. Both methods have limitations: WGBS is expensive and prohibitive for most large-scale projects; RRBS only interrogates 6-12% of the CpGs in the human genome. Here, we introduce methylation-sensitive restriction enzyme bisulfite sequencing (MREBS) which has the reduced sequencing requirements of RRBS, but significantly expands the coverage of CpG sites in the genome. We built a multiple regression model that combines the two features of MREBS: the bisulfite conversion ratios of single cytosines (as in WGBS and RRBS) as well as the number of reads that cover each locus (as in MRE-seq). This combined approach allowed us to estimate differential methylation across 60% of the genome using read count data alone, and where counts were sufficiently high in both samples (about 1.5% of the genome), our estimates were significantly improved by the single CpG conversion information. We show that differential DNA methylation values based on MREBS data correlate well with those based on WGBS and RRBS. This newly developed technique combines the sequencing cost of RRBS and DNA methylation estimates on a portion of the genome similar to WGBS, making it ideal for large-scale projects of mammalian genomes.
                Cover page: DNA methylation estimation using methylation-sensitive restriction enzyme bisulfite sequencing (MREBS)
                • Article
                • Peer Reviewed
                UCLA Previously Published Works (2021)

                Background

                The cell type composition of heterogeneous tissue samples can be a critical variable in both clinical and laboratory settings. However, current experimental methods of cell type quantification (e.g., cell flow cytometry) are costly, time consuming and have potential to introduce bias. Computational approaches that use expression data to infer cell type abundance offer an alternative solution. While these methods have gained popularity, most fail to produce accurate predictions for the full range of platforms currently used by researchers or for the wide variety of tissue types often studied.

                Results

                We present the Gene Expression Deconvolution Interactive Tool (GEDIT), a flexible tool that utilizes gene expression data to accurately predict cell type abundances. Using both simulated and experimental data, we extensively evaluate the performance of GEDIT and demonstrate that it returns robust results under a wide variety of conditions. These conditions include multiple platforms (microarray and RNA-seq), tissue types (blood and stromal), and species (human and mouse). Finally, we provide reference data from 8 sources spanning a broad range of stromal and hematopoietic types in both human and mouse. GEDIT also accepts user-submitted reference data, thus allowing the estimation of any cell type or subtype, provided that reference data are available.

                Conclusions

                GEDIT is a powerful method for evaluating the cell type composition of tissue samples and provides excellent accuracy and versatility compared to similar tools. The reference database provided here also allows users to obtain estimates for a wide variety of tissue samples without having to provide their own data.
                  Cover page: The Gene Expression Deconvolution Interactive Tool (GEDIT): accurate cell type quantification from gene expression data
                  • Article
                  • Peer Reviewed
                  UCLA Previously Published Works (2019)

                  Background

                  3' RNA sequencing provides an alternative to whole transcript analysis. However, we do not know a priori the relative advantage of each method. Thus, a comprehensive comparison between the whole transcript and the 3' method is needed to determine their relative merits. To this end, we used two commercially available library preparation kits, the KAPA Stranded mRNA-Seq kit (traditional method) and the Lexogen QuantSeq 3' mRNA-Seq kit (3' method), to prepare libraries from mouse liver RNA. We then sequenced and analyzed the libraries to determine the advantages and disadvantages of these two approaches.

                  Results

                  We found that the traditional whole transcript method and the 3' RNA-Seq method had similar levels of reproducibility. As expected, the whole transcript method assigned more reads to longer transcripts, while the 3' method assigned roughly equal numbers of reads to transcripts regardless of their lengths. We found that the 3' RNA-Seq method detected more short transcripts than the whole transcript method. With regard to differential expression analysis, we found that the whole transcript method detected more differentially expressed genes, regardless of the level of sequencing depth.

                  Conclusions

                  The 3' RNA-Seq method was better able to detect short transcripts, while the whole transcript RNA-Seq was able to detect more differentially expressed genes. Thus, both approaches have relative advantages and should be selected based on the goals of the experiment.
                    Cover page: A comparison between whole transcript and 3' RNA sequencing methods using Kapa and Lexogen library preparation methods.
                    • Article
                    • Peer Reviewed
                    UCLA Previously Published Works (2020)
                    Myeloid derived suppressor cells (MDSCs) are a population of immature myeloid cells that suppress adaptive immune function, yet the factors that regulate their suppressive function in patients with infection remain unclear. We studied MDSCs in patients with leprosy, a disease caused by Mycobacterium leprae, where clinical manifestations present on a spectrum that correlate with immunity to the pathogen. We found that HLA-DR-CD33+CD15+ MDSCs were increased in blood from patients with disseminated/progressive lepromatous leprosy and possessed T cell-suppressive activity as compared with self-limiting tuberculoid leprosy. Mechanistically, we found ER stress played a critical role in regulating the T cell suppressive activity in these MDSCs. Furthermore, ER stress augmented IL-10 production, contributing to MDSC activity, whereas IFN-γ allowed T cells to overcome MDSC suppressive activity. These studies highlight a regulatory mechanism that links ER stress to IL-10 in mediating MDSC suppressive function in human infectious disease.
                      Cover page: ER Stress Regulates Immunosuppressive Function of Myeloid Derived Suppressor Cells in Leprosy that Can Be Overcome in the Presence of IFN-γ
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