Stable RNA markers for identification of blood and saliva stains revealed from whole genome expression analysis of time-wise degraded samples

Human body fluids such as blood and saliva represent the most common source of biological material found at a crime scene. Reliable tissue identification in forensic science can reveal significant insights into crime scene reconstruction and can thus contribute toward solving crimes. Limitations of existing presumptive tests for body fluid identification in forensics, which are usually based on chemoluminescence or protein analysis, are expected to be overcome by RNA-based methods, provided that stable RNA markers with tissue-specific expression patterns are available. To generate sets of stable RNA markers for reliable identification of blood and saliva stains we (1) performed whole-genome gene expression analyses on a series of time-wise degraded blood and saliva stain samples using the Affymetrix U133 plus2 GeneChip, (2) consulted expression databases to obtain additional information on tissue specificity, and (3) confirmed expression patterns of the most promising candidate genes by quantitative real-time polymerase chain reaction including additional forensically relevant tissues such as semen and vaginal secretion. Overall, we identified nine stable mRNA markers for blood and five stable mRNA markers for saliva detection showing tissue-specific expression signals in stains aged up to 180 days of age, expectedly older. Although, all of the markers were able to differentiate blood/saliva from semen samples, none of them could differentiate vaginal secretion because of the complex nature of vaginal secretion and the biological similarity of buccal and vaginal mucosa. We propose the use of these 14 stable mRNA markers for identification of blood and saliva stains in future forensic practice

Species-specific responses during Seoul orthohantavirus infection in human and rat lung microvascular endothelial cells

Seoul orthohantavirus (SEOV) is a rat-borne zoonotic virus that is transmitted via inhalation of aerosolized infectious excreta, and can cause hemorrhagic fever with renal syndrome (HFRS) in humans worldwide. In rats, SEOV predominantly exists as a persistent infection in the absence of overt clinical signs. Lack of disease in rats is attributed to downregulation of pro-inflammatory and upregulation of regulatory host responses. As lung microvascular endothelial cells (LMECs) represent a primary target of infection in both human and rats, infections in these cells provide a unique opportunity to study the central role of LMECs in the dichotomy between pathogenicity in both species. In this study, host responses to SEOV infection in primary human and rat LMECs were directly compared on a transcriptional level. As infection of rat LMECs was more efficient than human LMECs, the majority of anti-viral defense responses were observed earlier in rat LMECs. Most prominently, SEOV-induced processes in both species included responses to cytokine stimulus, negative regulation of innate immune responses, responses to type I and II interferons, regulation of pattern recognition receptor signaling and MHC-I signaling. However, over time, in the rat LMECs, responses shifted from an anti-viral state towards a more immunotolerant state displayed by a PD-L1, B2M-, JAK2-focused interaction network aiding in negative regulation of cytotoxic CD8-positive T cell activation. This suggests a novel mechanism by which species-specific orthohantavirus-induced endothelium and T cell crosstalk may play a crucial role in the development of acute disease in humans and persistence in rodents.</p

Split Pool Ligation-based Single-cell Transcriptome sequencing (SPLiT-seq) data processing pipeline comparison

Background: Single-cell sequencing techniques are revolutionizing every field of biology by providing the ability to measure the abundance of biological molecules at a single-cell resolution. Although single-cell sequencing approaches have been developed for several molecular modalities, single-cell transcriptome sequencing is the most prevalent and widely applied technique. SPLiT-seq (split-pool ligation-based transcriptome sequencing) is one of these single-cell transcriptome techniques that applies a unique combinatorial-barcoding approach by splitting and pooling cells into multi-well plates containing barcodes. This unique approach required the development of dedicated computational tools to preprocess the data and extract the count matrices. Here we compare eight bioinformatic pipelines (alevin-fry splitp, LR-splitpipe, SCSit, splitpipe, splitpipeline, SPLiTseq-demultiplex, STARsolo and zUMI) that have been developed to process SPLiT-seq data. We provide an overview of the tools, their computational performance, functionality and impact on downstream processing of the single-cell data, which vary greatly depending on the tool used. Results: We show that STARsolo, splitpipe and alevin-fry splitp can all handle large amount of data within reasonable time. In contrast, the other five pipelines are slow when handling large datasets. When using smaller dataset, cell barcode results are similar with the exception of SPLiTseq-demultiplex and splitpipeline. LR-splitpipe that is originally designed for processing long-read sequencing data is the slowest of all pipelines. Alevin-fry produced different down-stream results that are difficult to interpret. STARsolo functions nearly identical to splitpipe and produce results that are highly similar to each other. However, STARsolo lacks the function to collapse random hexamer reads for which some additional coding is required. Conclusion: Our comprehensive comparative analysis aids users in selecting the most suitable analysis tool for efficient SPLiT-seq data processing, while also detailing the specific prerequisites for each of these pipelines. From the available pipelines, we recommend splitpipe or STARSolo for SPLiT-seq data analysis.</p

Species-specific responses during Seoul orthohantavirus infection in human and rat lung microvascular endothelial cells

Seoul orthohantavirus (SEOV) is a rat-borne zoonotic virus that is transmitted via inhalation of aerosolized infectious excreta, and can cause hemorrhagic fever with renal syndrome (HFRS) in humans worldwide. In rats, SEOV predominantly exists as a persistent infection in the absence of overt clinical signs. Lack of disease in rats is attributed to downregulation of pro-inflammatory and upregulation of regulatory host responses. As lung microvascular endothelial cells (LMECs) represent a primary target of infection in both human and rats, infections in these cells provide a unique opportunity to study the central role of LMECs in the dichotomy between pathogenicity in both species. In this study, host responses to SEOV infection in primary human and rat LMECs were directly compared on a transcriptional level. As infection of rat LMECs was more efficient than human LMECs, the majority of anti-viral defense responses were observed earlier in rat LMECs. Most prominently, SEOV-induced processes in both species included responses to cytokine stimulus, negative regulation of innate immune responses, responses to type I and II interferons, regulation of pattern recognition receptor signaling and MHC-I signaling. However, over time, in the rat LMECs, responses shifted from an anti-viral state towards a more immunotolerant state displayed by a PD-L1, B2M-, JAK2-focused interaction network aiding in negative regulation of cytotoxic CD8-positive T cell activation. This suggests a novel mechanism by which species-specific orthohantavirus-induced endothelium and T cell crosstalk may play a crucial role in the development of acute disease in humans and persistence in rodents.</p

Progesterone Inhibits Epithelial-to-Mesenchymal Transition in Endometrial Cancer

Background: Every year approximately 74,000 women die of endometrial cancer, mainly due to recurrent or metastatic disease. The presence of tumor infiltrating lymphocytes (TILs) as well as progesterone receptor (PR) positivity has been correlated with improved prognosis. This study describes two mechanisms by which progesterone inhibits metastatic spread of endometrial cancer: by stimulating T-cell infiltration and by inhibiting epithelial-to-mesenchymal cell transition (EMT). Methodology and Principal Findings: Paraffin sections from patients with (n = 9) or without (n = 9) progressive endometrial cancer (recurrent or metastatic disease) were assessed for the presence of CD4+ (helper), CD8+ (cytotoxic) and Foxp3+ (regulatory) T-lymphocytes and PR expression. Progressive disease was observed to be associated with significant loss of TILs and loss of PR expression. Frozen tumor samples, used for genome-wide expression analysis, showed significant regulation of pathways Conclusion: Intact progesterone signaling in non-progressive endometrial cancer seems to be an important factor stimulating immunosurveilance and inhibiting transition from an epithelial to a more mesenchymal, more invasive phenotype

Rabies virus uniquely reprograms the transcriptome of human monocyte-derived macrophages

Macrophages are amongst the first immune cells that encounter rabies virus (RABV) at virus entry sites. Activation of macrophages is essential for the onset of a potent immune response, but insights into the effects of RABV on macrophage activation are scarce. In this study we performed high-throughput sequencing on RNA extracted from macrophages that were exposed to RABV for 48 hours, and compared their transcriptional profiles to that of non-polarized macrophages (M0), and macrophages polarized towards the canonical M1, M2a and M2c phenotypes. Our analysis revealed that RABV-stimulated macrophages show high expression of several M1, M2a and M2c signature genes. Apart from their partial resemblance to these phenotypes, unbiased clustering analysis revealed that RABV induces a unique and distinct polarization program. Closer examination revealed that RABV induced multiple pathways related to the interferon- and antiviral response, which were not induced under other classical polarization strategies. Surprisingly, our data show that RABV induces an activated rather than a fully suppressed macrophage phenotype, triggering virus-induced activation and polarization. This includes multiple genes with known antiviral (e.g. APOBEC3A, IFIT/OAS/TRIM genes), which may play a role in anti-RABV immunity.</p

光子計数によるX線ラジオグラフィ

博士（工学）神戸大

Identification of candidate enhancers controlling the transcriptome during the formation of interphalangeal joints

The formation of the synovial joint begins with the visible emergence of a stripe of densely packed mesenchymal cells located between distal ends of the developing skeletal anlagen called the interzone. Recently the transcriptome of the early synovial joint was reported. Knowledge about enhancers would complement these data and lead to a better understanding of the control of gene transcription at the onset of joint development. Using ChIP-sequencing we have mapped the H3-signatures H3K27ac and H3K4me1 to locate regulatory elements specific for the interzone and adjacent phalange, respectively. This one-stage atlas of candidate enhancers (CEs) was used to map the association between these respective joint tissue specific CEs and biological processes. Subsequently, integrative analysis of transcriptomic data and CEs identified new putative regulatory elements of genes expressed in interzone (e.g., GDF5, BMP2 and DACT2) and phalange (e.g., MATN1, HAPLN1 and SNAI1). We also linked such CEs to genes known as crucial in synovial joint hypermobility and osteoarthritis, as well as phalange malformations. These analyses show that the CE atlas can serve as resource for identifying, and as starting point for experimentally validating, putative disease-causing genomic regulatory regions in patients with synovial joint dysfunctions and/or phalange disorders, and enhancer-controlled synovial joint and phalange formation

Single-Cell RNA Sequencing of Donor-Reactive T Cells Reveals Role of Apoptosis in Donor-Specific Hyporesponsiveness of Kidney Transplant Recipients

After kidney transplantation (KT), donor-specific hyporesponsiveness (DSH) of recipient T cells develops over time. Recently, apoptosis was identified as a possible underlying mechanism. In this study, both transcriptomic profiles and complete V(D)J variable regions of TR transcripts from individual alloreactive T cells of kidney transplant recipients were determined with single-cell RNA sequencing. Alloreactive T cells were identified by CD137 expression after stimulation of peripheral blood mononuclear cells obtained from KT recipients (N = 7) prior to and 3–5 years after transplantation with cells of their donor or a third party control. The alloreactive T cells were sorted, sequenced and the transcriptome and T cell receptor profiles were analyzed using unsupervised clustering. Alloreactive T cells retain a highly polyclonal T Cell Receptor Alpha/Beta repertoire over time. Post transplantation, donor-reactive CD4+ T cells had a specific downregulation of genes involved in T cell cytokine-mediated pathways and apoptosis. The CD8+ donor-reactive T cell profile did not change significantly over time. Single-cell expression profiling shows that activated and pro-apoptotic donor-reactive CD4+ T cell clones are preferentially lost after transplantation in stable kidney transplant recipients.</p

Comparison of Single Cell Transcriptome Sequencing Methods:Of Mice and Men

Single cell RNAseq has been a big leap in many areas of biology. Rather than investigating gene expression on a whole organism level, this technology enables scientists to get a detailed look at rare single cells or within their cell population of interest. The field is growing, and many new methods appear each year. We compared methods utilized in our core facility: Smart-seq3, PlexWell, FLASH-seq, VASA-seq, SORT-seq, 10X, Evercode, and HIVE. We characterized the equipment requirements for each method. We evaluated the performances of these methods based on detected features, transcriptome diversity, mitochondrial RNA abundance and multiplets, among others and benchmarked them against bulk RNA sequencing. Here, we show that bulk transcriptome detects more unique transcripts than any single cell method. While most methods are comparable in many regards, FLASH-seq and VASA-seq yielded the best metrics, e.g., in number of features. If no equipment for automation is available or many cells are desired, then HIVE or 10X yield good results. In general, more recently developed methods perform better. This also leads to the conclusion that older methods should be phased out, and that the development of single cell RNAseq methods is still progressing considerably.</p