scholarly journals Clinical Ketosis-Associated Alteration of Gene Expression in Holstein Cows

Genes ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 219 ◽  
Author(s):  
Zhou-Lin Wu ◽  
Shi-Yi Chen ◽  
Chao Qin ◽  
Xianbo Jia ◽  
Feilong Deng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dairy Cows ◽  
Molecular Mechanisms ◽  
Transition Period ◽  
Expression Patterns ◽  
Ion Homeostasis ◽  
Blood Samples ◽  
Biological Stress ◽  
Altered Gene ◽  
And Control

Ketosis is one of the most prevalent transition metabolic disorders in dairy cows, and has been intrinsically influenced by both genetic and nutritional factors. However, altered gene expression with respective to dairy cow ketosis has not been addressed yet, especially at the genome-wide level. In this study, we recruited nine Holsteins diagnosed with clinical ketosis and ten healthy controls, for which whole blood samples were collected at both prepartum and postpartum. Four groups of blood samples were defined: from cows with ketosis at prepartum (PCK, N = 9) and postpartum (CK, N = 9), respectively, and controls at prepartum (PHC, N = 10) and postpartum (HC, N = 10). RNA-Seq approach was used for investigating gene expression, by which a total of 27,233 genes were quantified with four billion high-quality reads. Subsequently, we revealed 75 and four differentially expressed genes (DEGs) between sick and control cows at postpartum and prepartum, respectively, which indicated that sick and control cows had similar gene expression patterns at prepartum. Meanwhile, there were 95 DEGs between postpartum and prepartum for sick cows, which showed depressed changes of gene expression during this transition period in comparison with healthy cows (428 DEGs). Functional analyses revealed the associated DEGs with ketosis were mainly involved in biological stress response, ion homeostasis, AA metabolism, energy signaling, and disease related pathways. Finally, we proposed that the expression level of STX1A would be potentially used as a new biomarker because it was the only gene that was highly expressed in sick cows at both prepartum and postpartum. These results could significantly help us to understand the underlying molecular mechanisms for incidence and progression of ketosis in dairy cows.

Circulating melanoma cells isolated from clinical blood samples and characterized by full-length mRNA sequencing at single-cell level.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 10539-10539 ◽  
Author(s):  
Yu-Chieh Wang ◽  
Daniel Ramskold ◽  
Shujun Luo ◽  
Robin Li ◽  
Qiaolin Deng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Melanoma Cells ◽  
Clinical Samples ◽  
Single Cell Level ◽  
Cell Level ◽  
Blood Samples

10539 Background: Melanoma is the most aggressive type of skin cancer. Late-stage melanoma is highly metastatic and currently lacks effective treatment. This discouraging clinical observation highlights the need for a better understanding of the molecular mechanisms underlying melanoma initiation and progression and for developing new therapeutic approaches based on novel targets. Although genome-wide transcriptome analyses have been frequently used to study molecular alterations in clinical samples, it has been technically challenging to obtain the transcriptomic profiles at single-cell level. Methods: Using antibody-mediated magnetic activated cell separation (MACS), we isolated and individualized putative circulating melanoma cells (CMCs) from the blood samples of the melanoma patients at advance stages. The transcriptomic analysis based on a novel and robust mRNA-Seq protocol (Smart-Seq) was established and applied to the putative CMCs for single-cell profiling. Results: We have discovered distinct gene expression patterns, including new putative markers for CMCs. Meanwhile, the gene expression profiles derived of the CMC candidates isolated from the patient’s blood samples are closely-related to the expression profiles of other cells originated from human melanocytes, including normal melanocytes in primary culture and melanoma cell lines. Compared with existing methods, Smart-Seq has improved read coverage across transcripts, which provides advantage for better analyzing transcript isoforms and SNPs. Conclusions: Our results suggest that the techniques developed in this research for cell isolation and transcriptomic analyses can potentially be used for addressing many biological and clinical questions requiring genomewide transcriptome profiling in rare cells.

scholarly journals A combination approach of pseudotime analysis and mathematical modeling for understanding drug-resistant mechanisms

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shigeyuki Magi ◽  
Sewon Ki ◽  
Masao Ukai ◽  
Elisa Domínguez-Hüttinger ◽  
Atsuhiko T Naito ◽  
...  
Keyword(s):  
Gene Expression ◽  
Drug Resistance ◽  
Cancer Cells ◽  
Metabolic Regulation ◽  
Sequential Analysis ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Tamoxifen Resistance ◽  
Equation Model ◽  
Altered Gene

AbstractCancer cells acquire drug resistance through the following stages: nonresistant, pre-resistant, and resistant. Although the molecular mechanism of drug resistance is well investigated, the process of drug resistance acquisition remains largely unknown. Here we elucidate the molecular mechanisms underlying the process of drug resistance acquisition by sequential analysis of gene expression patterns in tamoxifen-treated breast cancer cells. Single-cell RNA-sequencing indicates that tamoxifen-resistant cells can be subgrouped into two, one showing altered gene expression related to metabolic regulation and another showing high expression levels of adhesion-related molecules and histone-modifying enzymes. Pseudotime analysis showed a cell transition trajectory to the two resistant subgroups that stem from a shared pre-resistant state. An ordinary differential equation model based on the trajectory fitted well with the experimental results of cell growth. Based on the established model, it was predicted and experimentally validated that inhibition of transition to both resistant subtypes would prevent the appearance of tamoxifen resistance.

scholarly journals A Combination Approach of Pseudotime Analysis And Mathematical Modeling For Understanding The Drug-Resistant Mechanisms

2021 ◽  
Author(s):  
Shigeyuki Magi ◽  
Sewon Ki ◽  
Masao Ukai ◽  
Elisa Domínguez-Hüttinger ◽  
Atsuhiko Naito ◽  
...  
Keyword(s):  
Gene Expression ◽  
Drug Resistance ◽  
Cancer Cells ◽  
Metabolic Regulation ◽  
Sequential Analysis ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Tamoxifen Resistance ◽  
Equation Model ◽  
Altered Gene

Abstract Cancer cells acquire drug resistance through the following nonresistant, pre-resistant, and resistant stages. Although the molecular mechanism of drug resistance is well investigated, the process of drug resistance acquisition remains largely unknown. Here we elucidate the molecular mechanisms underlying the process of drug resistance acquisition by sequential analysis of gene expression patterns in tamoxifen-treated breast cancer cells. Single-cell RNA-sequencing indicates that tamoxifen-resistant cells can be subgrouped into two, one showing altered gene expression related to metabolic regulation. The other showed high expression levels of adhesion-related molecules and histone-modifying enzymes. Pseudotime analysis showed a cell transition trajectory to the two resistant subgroups that stem from a shared pre-resistant state. An ordinary differential equation model based on the trajectory fitted well with the experimental results of cell growth. Based on the established model, it was predicted and experimentally validated that inhibition of transition to both resistant subtypes would prevent the appearance of tamoxifen resistance.

scholarly journals The Physiological Roles of Vitamin E and Hypovitaminosis E in the Transition Period of High-Yielding Dairy Cows

Animals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1088
Author(s):  
Satoshi Haga ◽  
Hiroshi Ishizaki ◽  
Sanggun Roh
Keyword(s):  
Dairy Cows ◽  
High Performance ◽  
Molecular Mechanisms ◽  
Transition Period ◽  
Disease Risk ◽  
Serum Vitamin ◽  
Physiological Role ◽  
Density Lipoprotein ◽  
Alpha Tocopherol ◽  
Transition Dairy Cows

Levels of alpha-tocopherol (α-Toc) decline gradually in blood throughout prepartum, reaching lowest levels (hypovitaminosis E) around calving. Despite numerous reports about the disease risk in hypovitaminosis E and the effect of α-Toc supplementation on the health of transition dairy cows, its risk and supplemental effects are controversial. Here, we present some novel data about the disease risk of hypovitaminosis E and the effects of α-Toc supplementation in transition dairy cows. These data strongly demonstrate that hypovitaminosis E is a risk factor for the occurrence of peripartum disease. Furthermore, a study on the effectiveness of using serum vitamin levels as biomarkers to predict disease in dairy cows was reported, and a rapid field test for measuring vitamin levels was developed. By contrast, evidence for how hypovitaminosis E occurred during the transition period was scarce until the 2010s. Pioneering studies conducted with humans and rodents have identified and characterised some α-Toc-related proteins, molecular players involved in α-Toc regulation followed by a study in ruminants from the 2010s. Based on recent literature, the six physiological factors: (1) the decline in α-Toc intake from the close-up period; (2) changes in the digestive and absorptive functions of α-Toc; (3) the decline in plasma high-density lipoprotein as an α-Toc carrier; (4) increasing oxidative stress and consumption of α-Toc; (5) decreasing hepatic α-Toc transfer to circulation; and (6) increasing mammary α-Toc transfer from blood to colostrum, may be involved in α-Toc deficiency during the transition period. However, the mechanisms and pathways are poorly understood, and further studies are needed to understand the physiological role of α-Toc-related molecules in cattle. Understanding the molecular mechanisms underlying hypovitaminosis E will contribute to the prevention of peripartum disease and high performance in dairy cows.

Altered gene expression patterns in ART offspring

2004 ◽  
Vol 82 ◽  
pp. S292 ◽  
Author(s):  
H.J. Kang ◽  
Y. Katagiri ◽  
Q.V. Neri ◽  
R. Baergen ◽  
Z. Rosenwaks ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Altered Gene Expression ◽  
Altered Gene

scholarly journals Bioinformatic analysis identifies potential biomarkers and therapeutic targets of septic-shock-associated acute kidney injury

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Yun Tang ◽  
Xiaobo Yang ◽  
Huaqing Shu ◽  
Yuan Yu ◽  
Shangwen Pan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Septic Shock ◽  
Acute Kidney Injury ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Kidney Injury ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Blood Samples ◽  
Potential Biomarkers

Abstract Background Sepsis and septic shock are life-threatening diseases with high mortality rate in intensive care unit (ICU). Acute kidney injury (AKI) is a common complication of sepsis, and its occurrence is a poor prognostic sign to septic patients. We analyzed co-differentially expressed genes (co-DEGs) to explore relationships between septic shock and AKI and reveal potential biomarkers and therapeutic targets of septic-shock-associated AKI (SSAKI). Methods Two gene expression datasets (GSE30718 and GSE57065) were downloaded from the Gene Expression Omnibus (GEO). The GSE57065 dataset included 28 septic shock patients and 25 healthy volunteers and blood samples were collected within 0.5, 24 and 48 h after shock. Specimens of GSE30718 were collected from 26 patients with AKI and 11 control patents. AKI-DEGs and septic-shock-DEGs were identified using the two datasets. Subsequently, Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs. We also evaluated co-DEGs and corresponding predicted miRNAs involved in septic shock and AKI. Results We identified 62 DEGs in AKI specimens and 888, 870, and 717 DEGs in septic shock blood samples within 0.5, 24 and 48 h, respectively. The hub genes of EGF and OLFM4 may be involved in AKI and QPCT, CKAP4, PRKCQ, PLAC8, PRC1, BCL9L, ATP11B, KLHL2, LDLRAP1, NDUFAF1, IFIT2, CSF1R, HGF, NRN1, GZMB, and STAT4 may be associated with septic shock. Besides, co-DEGs of VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 coupled with corresponding predicted miRNAs, especially miR-29b-3p, miR-152-3p, and miR-223-3p may be regarded as promising targets for the diagnosis and treatment of SSAKI in the future. Conclusions Septic shock and AKI are related and VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 genes are significantly associated with novel biomarkers involved in the occurrence and development of SSAKI.

scholarly journals Integrative Transcriptomics Reveals Activation of Innate Immune Responses and Inhibition of Inflammation During Oral Immunotherapy for Egg Allergy in Children

2021 ◽  
Vol 12 ◽  
Author(s):  
Piia Karisola ◽  
Kati Palosuo ◽  
Victoria Hinkkanen ◽  
Lukas Wisgrill ◽  
Terhi Savinko ◽  
...  
Keyword(s):  
Gene Expression ◽  
Clinical Outcome ◽  
Immune Responses ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Oral Immunotherapy ◽  
Innate Immune ◽  
Egg Allergy ◽  
Innate Immune Responses ◽  
Open Label

We previously reported the results of a randomized, open-label trial of egg oral immunotherapy (OIT) in 50 children where 44% were desensitized and 46% were partially desensitized after 8 months of treatment. Here we focus on cell-mediated molecular mechanisms driving desensitization during egg OIT. We sought to determine whether changes in genome-wide gene expression in blood cells during egg OIT correlate with humoral responses and the clinical outcome. The blood cell transcriptome of 50 children receiving egg OIT was profiled using peripheral blood mononuclear cell (PBMC) samples obtained at baseline and after 3 and 8 months of OIT. We identified 467 differentially expressed genes (DEGs) after 3 or 8 months of egg OIT. At 8 months, 86% of the DEGs were downregulated and played a role in the signaling of TREM1, IL-6, and IL-17. In correlation analyses, Gal d 1–4-specific IgG4 antibodies associated positively with DEGs playing a role in pathogen recognition and antigen presentation and negatively with DEGs playing a role in the signaling of IL-10, IL-6, and IL-17. Desensitized and partially desensitized patients had differences in their antibody responses, and although most of the transcriptomic changes were shared, both groups had also specific patterns, which suggest slower changes in partially desensitized and activation of NK cells in the desensitized group. OIT for egg allergy in children inhibits inflammation and activates innate immune responses regardless of the clinical outcome at 8 months. Changes in gene expression patterns first appear as posttranslational protein modifications, followed by more sustained epigenetic gene regulatory functions related to successful desensitization.

scholarly journals An animal model study on the gene expression profile of meniscal degeneration

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yehan Fang ◽  
Hui Huang ◽  
Gang Zhou ◽  
Qinghua Wang ◽  
Feng Gao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pathway Analysis ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Control Group ◽  
Ion Binding ◽  
Endoplasmic Reticulum Membrane ◽  
Rt Pcr ◽  
Go Analysis ◽  
Meniscal Degeneration

AbstractMeniscal degeneration is a very common condition in elderly individuals, but the underlying mechanisms of its occurrence are not completely clear. This study examines the molecular mechanisms of meniscal degeneration. The anterior cruciate ligament (ACL) and lateral collateral ligament (LCL) of the right rear limbs of seven Wuzhishan mini-pigs were resected (meniscal degeneration group), and the left rear legs were sham-operated (control group). After 6 months, samples were taken for gene chip analysis, including differentially expressed gene (DEG) analysis, gene ontology (GO) analysis, clustering analysis, and pathway analysis. The selected 12 DEGs were validated by real time reverse transcription-polymerase chain reaction (RT-PCR). The two groups showed specific and highly clustered DEGs. A total of 893 DEGs were found, in which 537 are upregulated, and 356 are downregulated. The GO analysis showed that the significantly affected biological processes include nitric oxide metabolic process, male sex differentiation, and mesenchymal morphogenesis, the significantly affected cellular components include the endoplasmic reticulum membrane, and the significantly affected molecular functions include transition metal ion binding and iron ion binding. The pathway analysis showed that the significantly affected pathways include type II diabetes mellitus, inflammatory mediator regulation of TRP channels, and AMPK signaling pathway. The results of RT-PCR indicate that the microarray data accurately reflects the gene expression patterns. These findings indicate that several molecular mechanisms are involved in the development of meniscal degeneration, thus improving our understanding of meniscal degeneration and provide molecular therapeutic targets in the future.

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