Genetic and molecular expression patterns in critical illness

2016 ◽  
Author(s):  
Anthony F. Suffredini ◽  
J. Perren Cobb
Keyword(s):  
Critical Illness ◽  
Host Response ◽  
Expression Patterns ◽  
Host Responses ◽  
Critical Event ◽  
Severe Illness ◽  
Genome Wide ◽  
Patients At Risk ◽  
Molecular Expression ◽  
Acute Nature

Investigators who study RNA, proteins, or metabolites use analytic platforms that simultaneously measure changes in the relative abundance of thousands of molecules in a single biological sample. Over the last decade, the application of these high-throughput, genome-wide platforms to study critical illness and injury has generated huge quantities of data that require specialized computational skills for analysis. These investigations hold promise for improving our understanding of the host response, thereby transforming the practice of intensive care. This chapter summarizes recent technological and computational approaches used in genomics, proteomics, and metabolomics. While major advances have been made with these approaches when applied to chronic diseases, the acute nature of critical illness and injury has unique challenges. The rapidity of initiating events, the trajectory of inflammation that follows injury or infection and the interplay of host responses to a replicating infection, all have major effects on changes in gene and molecular expression. This complexity is further accentuated by measurement that may vary with the timing and type of tissue sampled after the critical event. In addition, the hunt for novel molecular markers holds promise for identifying patients at risk for severe illness and for enabling more individualized therapy.

scholarly journals Viral RNA load in plasma is associated with critical illness and a dysregulated host response in COVID-19

Critical Care ◽  
2020 ◽  
Vol 24 (1) ◽  
Author(s):  
Jesús F. Bermejo-Martin ◽  
Milagros González-Rivera ◽  
Raquel Almansa ◽  
Dariela Micheloud ◽  
Ana P. Tedim ◽  
...  
Keyword(s):  
Critical Illness ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Host Response ◽  
Correlation Coefficients ◽  
Digital Pcr ◽  
Viral Rna ◽  
Host Responses ◽  
Nucleoprotein Gene ◽  
Pcr Targeting

Abstract Background COVID-19 can course with respiratory and extrapulmonary disease. SARS-CoV-2 RNA is detected in respiratory samples but also in blood, stool and urine. Severe COVID-19 is characterized by a dysregulated host response to this virus. We studied whether viral RNAemia or viral RNA load in plasma is associated with severe COVID-19 and also to this dysregulated response. Methods A total of 250 patients with COVID-19 were recruited (50 outpatients, 100 hospitalized ward patients and 100 critically ill). Viral RNA detection and quantification in plasma was performed using droplet digital PCR, targeting the N1 and N2 regions of the SARS-CoV-2 nucleoprotein gene. The association between SARS-CoV-2 RNAemia and viral RNA load in plasma with severity was evaluated by multivariate logistic regression. Correlations between viral RNA load and biomarkers evidencing dysregulation of host response were evaluated by calculating the Spearman correlation coefficients. Results The frequency of viral RNAemia was higher in the critically ill patients (78%) compared to ward patients (27%) and outpatients (2%) (p < 0.001). Critical patients had higher viral RNA loads in plasma than non-critically ill patients, with non-survivors showing the highest values. When outpatients and ward patients were compared, viral RNAemia did not show significant associations in the multivariate analysis. In contrast, when ward patients were compared with ICU patients, both viral RNAemia and viral RNA load in plasma were associated with critical illness (OR [CI 95%], p): RNAemia (3.92 [1.183–12.968], 0.025), viral RNA load (N1) (1.962 [1.244–3.096], 0.004); viral RNA load (N2) (2.229 [1.382–3.595], 0.001). Viral RNA load in plasma correlated with higher levels of chemokines (CXCL10, CCL2), biomarkers indicative of a systemic inflammatory response (IL-6, CRP, ferritin), activation of NK cells (IL-15), endothelial dysfunction (VCAM-1, angiopoietin-2, ICAM-1), coagulation activation (D-Dimer and INR), tissue damage (LDH, GPT), neutrophil response (neutrophils counts, myeloperoxidase, GM-CSF) and immunodepression (PD-L1, IL-10, lymphopenia and monocytopenia). Conclusions SARS-CoV-2 RNAemia and viral RNA load in plasma are associated with critical illness in COVID-19. Viral RNA load in plasma correlates with key signatures of dysregulated host responses, suggesting a major role of uncontrolled viral replication in the pathogenesis of this disease.

scholarly journals Viral RNA load in plasma is associated with critical illness and a dysregulated host response in COVID-19

2020 ◽  
Author(s):  
Jesús F Bermejo-Martin ◽  
Milagros González-Rivera ◽  
Raquel Almansa ◽  
Dariela Micheloud ◽  
Ana P. Tedim ◽  
...  
Keyword(s):  
Critical Illness ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Host Response ◽  
Correlation Coefficients ◽  
Digital Pcr ◽  
Viral Rna ◽  
Host Responses ◽  
Nucleoprotein Gene ◽  
Pcr Targeting

AbstractBackgroundCOVID-19 can course with respiratory and extrapulmonary disease. SARS-CoV-2 RNA is detected in respiratory samples but also in blood, stool and urine. Severe COVID-19 is characterised by a dysregulated host response to this virus. We studied whether viral RNAemia or viral RNA load in plasma are associated to severe COVID-19 and also to this dysregulated response.Methods250 patients with COVID-19 were recruited (50 outpatients, 100 hospitalised ward patients, and 100 critically ill). Viral RNA detection and quantification in plasma was performed using droplet digital PCR, targeting the N1 and N2 regions of the SARS-CoV-2 nucleoprotein gene. The association between SARS-CoV-2 RNAemia and viral RNA load in plasma with severity was evaluated by multivariate logistic regression. Correlations between viral RNA load and biomarkers evidencing dysregulation of host response were evaluated by calculating the Spearman correlation coefficients.Resultsthe frequency of viral RNAemia was higher in the critically ill patients (78%) compared to ward patients (27%) and outpatients (2%) (p<0.001). Critical patients had higher viral RNA loads in plasma than non-critically ill patients, with non survivors showing the highest values. When outpatients and ward patients were compared, viral RNAemia did not show significant associations in the multivariate analysis. In contrast, when ward patients were compared with ICU patients, both viral RNAemia and viral RNA load in plasma were associated with critical illness (OR [CI 95%], p): RNAemia (3.92 [1.183 - 12.968], 0.025), viral RNA load (N1) (1.962 [1.244 - 3.096], 0.004); viral RNA load (N2) (2.229 [1.382 - 3.595], 0.001). Viral RNA load in plasma correlated with higher levels of chemokines (CXCL10, CCL2), biomarkers indicative of a systemic inflammatory response (IL-6, CRP, Ferritin), activation of NK cells (IL-15), endothelial dysfunction (VCAM-1, angiopoietin-2, ICAM-1), coagulation activation (D-Dimer and INR), tissue damage (LDH, GPT), neutrophil response (neutrophils counts, myeloperoxidase, GM-CSF) and immunodepression (PD-L1, IL-10, lymphopenia and monocytopenia).ConclusionsSARS-CoV-2 RNAemia and viral RNA load in plasma are associated to critical illness in COVID-19. Viral RNA load in plasma correlates with key signatures of dysregulated host responses, suggesting a major role of uncontrolled viral replication in the pathogenesis of this disease.

scholarly journals Immune Subtyping in Latent Tuberculosis

2021 ◽  
Vol 12 ◽  
Author(s):  
Ushashi Banerjee ◽  
Priyanka Baloni ◽  
Amit Singh ◽  
Nagasuma Chandra
Keyword(s):  
Host Response ◽  
Latent Infection ◽  
Expression Profiles ◽  
Latent Tuberculosis ◽  
Gene Expression Profiles ◽  
Deep Understanding ◽  
Host Responses ◽  
Network Mining ◽  
Genome Wide ◽  
Latently Infected

Latent tuberculosis infection (LTBI) poses a major roadblock in the global effort to eradicate tuberculosis (TB). A deep understanding of the host responses involved in establishment and maintenance of TB latency is required to propel the development of sensitive methods to detect and treat LTBI. Given that LTBI individuals are typically asymptomatic, it is challenging to differentiate latently infected from uninfected individuals. A major contributor to this problem is that no clear pattern of host response is linked with LTBI, as molecular correlates of latent infection have been hard to identify. In this study, we have analyzed the global perturbations in host response in LTBI individuals as compared to uninfected individuals and particularly the heterogeneity in such response, across LTBI cohorts. For this, we constructed individualized genome-wide host response networks informed by blood transcriptomes for 136 LTBI cases and have used a sensitive network mining algorithm to identify top-ranked host response subnetworks in each case. Our analysis indicates that despite the high heterogeneity in the gene expression profiles among LTBI samples, clear patterns of perturbation are found in the immune response pathways, leading to grouping LTBI samples into 4 different immune-subtypes. Our results suggest that different subnetworks of molecular perturbations are associated with latent tuberculosis.

scholarly journals Genome-Wide Transcriptomic Identification and Functional Insight of Lily WRKY Genes Responding to Botrytis Fungal Disease

Plants ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 776
Author(s):  
Shipra Kumari ◽  
Bashistha Kumar Kanth ◽  
Ju young Ahn ◽  
Jong Hwa Kim ◽  
Geung-Joo Lee
Keyword(s):  
Abiotic Stress ◽  
Biotic Stress ◽  
Developmental Stages ◽  
Expression Patterns ◽  
Lilium Longiflorum ◽  
Biotic And Abiotic Stress ◽  
Biotic Stresses ◽  
Genome Wide

Genome-wide transcriptome analysis using RNA-Seq of Lilium longiflorum revealed valuable genes responding to biotic stresses. WRKY transcription factors are regulatory proteins playing essential roles in defense processes under environmental stresses, causing considerable losses in flower quality and production. Thirty-eight WRKY genes were identified from the transcriptomic profile from lily genotypes, exhibiting leaf blight caused by Botrytis elliptica. Lily WRKYs have a highly conserved motif, WRKYGQK, with a common variant, WRKYGKK. Phylogeny of LlWRKYs with homologous genes from other representative plant species classified them into three groups- I, II, and III consisting of seven, 22, and nine genes, respectively. Base on functional annotation, 22 LlWRKY genes were associated with biotic stress, nine with abiotic stress, and seven with others. Sixteen unique LlWRKY were studied to investigate responses to stress conditions using gene expression under biotic and abiotic stress treatments. Five genes—LlWRKY3, LlWRKY4, LlWRKY5, LlWRKY10, and LlWRKY12—were substantially upregulated, proving to be biotic stress-responsive genes in vivo and in vitro conditions. Moreover, the expression patterns of LlWRKY genes varied in response to drought, heat, cold, and different developmental stages or tissues. Overall, our study provides structural and molecular insights into LlWRKY genes for use in the genetic engineering in Lilium against Botrytis disease.

scholarly journals Roles of the 14-3-3 gene family in cotton flowering

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Na Sang ◽  
Hui Liu ◽  
Bin Ma ◽  
Xianzhong Huang ◽  
Lu Zhuo ◽  
...  
Keyword(s):  
Gene Family ◽  
Protein Interactions ◽  
Leucine Zipper ◽  
Expression Patterns ◽  
Bimolecular Fluorescence Complementation ◽  
Structural Motif ◽  
Virus Induced Gene Silencing ◽  
Protein Protein Interactions ◽  
Basic Leucine Zipper ◽  
Genome Wide

Abstract Background In plants, 14-3-3 proteins, also called GENERAL REGULATORY FACTORs (GRFs), encoded by a large multigene family, are involved in protein–protein interactions and play crucial roles in various physiological processes. No genome-wide analysis of the GRF gene family has been performed in cotton, and their functions in flowering are largely unknown. Results In this study, 17, 17, 31, and 17 GRF genes were identified in Gossypium herbaceum, G. arboreum, G. hirsutum, and G. raimondii, respectively, by genome-wide analyses and were designated as GheGRFs, GaGRFs, GhGRFs, and GrGRFs, respectively. A phylogenetic analysis revealed that these proteins were divided into ε and non-ε groups. Gene structural, motif composition, synteny, and duplicated gene analyses of the identified GRF genes provided insights into the evolution of this family in cotton. GhGRF genes exhibited diverse expression patterns in different tissues. Yeast two-hybrid and bimolecular fluorescence complementation assays showed that the GhGRFs interacted with the cotton FLOWERING LOCUS T homologue GhFT in the cytoplasm and nucleus, while they interacted with the basic leucine zipper transcription factor GhFD only in the nucleus. Virus-induced gene silencing in G. hirsutum and transgenic studies in Arabidopsis demonstrated that GhGRF3/6/9/15 repressed flowering and that GhGRF14 promoted flowering. Conclusions Here, 82 GRF genes were identified in cotton, and their gene and protein features, classification, evolution, and expression patterns were comprehensively and systematically investigated. The GhGRF3/6/9/15 interacted with GhFT and GhFD to form florigen activation complexs that inhibited flowering. However, GhGRF14 interacted with GhFT and GhFD to form florigen activation complex that promoted flowering. The results provide a foundation for further studies on the regulatory mechanisms of flowering.

scholarly journals Shedding Light on the African Enigma: In Vitro Testing of Homo sapiens-Helicobacter pylori Coevolution

2021 ◽  
Vol 9 (2) ◽  
pp. 240
Author(s):  
Bruno Cavadas ◽  
Marina Leite ◽  
Nicole Pedro ◽  
Ana C. Magalhães ◽  
Joana Melo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Helicobacter Pylori ◽  
Host Response ◽  
Homo Sapiens ◽  
European Ancestry ◽  
Genome Wide ◽  
Expression Host ◽  
H Pylori ◽  
Human Ancestry

The continuous characterization of genome-wide diversity in population and case–cohort samples, allied to the development of new algorithms, are shedding light on host ancestry impact and selection events on various infectious diseases. Especially interesting are the long-standing associations between humans and certain bacteria, such as the case of Helicobacter pylori, which could have been strong drivers of adaptation leading to coevolution. Some evidence on admixed gastric cancer cohorts have been suggested as supporting Homo-Helicobacter coevolution, but reliable experimental data that control both the bacterium and the host ancestries are lacking. Here, we conducted the first in vitro coinfection assays with dual human- and bacterium-matched and -mismatched ancestries, in African and European backgrounds, to evaluate the genome wide gene expression host response to H. pylori. Our results showed that: (1) the host response to H. pylori infection was greatly shaped by the human ancestry, with variability on innate immune system and metabolism; (2) African human ancestry showed signs of coevolution with H. pylori while European ancestry appeared to be maladapted; and (3) mismatched ancestry did not seem to be an important differentiator of gene expression at the initial stages of infection as assayed here.

scholarly journals Genome-wide identification and expression analysis of Raffinose synthetase family in cotton

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ruifeng Cui ◽  
Xiaoge Wang ◽  
Waqar Afzal Malik ◽  
Xuke Lu ◽  
Xiugui Chen ◽  
...  
Keyword(s):  
Abiotic Stress ◽  
Expression Patterns ◽  
Regulatory Elements ◽  
Plant Leaves ◽  
Motif Analysis ◽  
Expression Levels ◽  
Genome Wide ◽  
Salt And Drought Stress ◽  
Key Genes ◽  
Stress Gene

Abstract Background The Raffinose synthetase (RAFS) genes superfamily is critical for the synthesis of raffinose, which accumulates in plant leaves under abiotic stress. However, it remains unclear whether RAFS contributes to resistance to abiotic stress in plants, specifically in the Gossypium species. Results In this study, we identified 74 RAFS genes from G. hirsutum, G. barbadense, G. arboreum and G. raimondii by using a series of bioinformatic methods. Phylogenetic analysis showed that the RAFS gene family in the four Gossypium species could be divided into four major clades; the relatively uniform distribution of the gene number in each species ranged from 12 to 25 based on species ploidy, most likely resulting from an ancient whole-genome polyploidization. Gene motif analysis showed that the RAFS gene structure was relatively conservative. Promoter analysis for cis-regulatory elements showed that some RAFS genes might be regulated by gibberellins and abscisic acid, which might influence their expression levels. Moreover, we further examined the functions of RAFS under cold, heat, salt and drought stress conditions, based on the expression profile and co-expression network of RAFS genes in Gossypium species. Transcriptome analysis suggested that RAFS genes in clade III are highly expressed in organs such as seed, root, cotyledon, ovule and fiber, and under abiotic stress in particular, indicating the involvement of genes belonging to clade III in resistance to abiotic stress. Gene co-expressed network analysis showed that GhRFS2A-GhRFS6A, GhRFS6D, GhRFS7D and GhRFS8A-GhRFS11A were key genes, with high expression levels under salt, drought, cold and heat stress. Conclusion The findings may provide insights into the evolutionary relationships and expression patterns of RAFS genes in Gossypium species and a theoretical basis for the identification of stress resistance materials in cotton.

Genome-wide identification and analysis of the MADS-box gene family and its potential role in fruit ripening in black raspberry (Rubus occidentalis L.)

2021 ◽  
pp. 1-15
Author(s):  
Yaqiong Wu ◽  
Chunhong Zhang ◽  
Wenlong Wu ◽  
Weilin Li ◽  
Lianfei Lyu
Keyword(s):  
Gene Family ◽  
Fruit Ripening ◽  
Fruit Development ◽  
Expression Patterns ◽  
Type I ◽  
Black Raspberry ◽  
Mads Box ◽  
Mads Box Genes ◽  
Genome Wide ◽  
Mads Box Gene

BACKGROUND: Black raspberry is a vital fruit crop with a high antioxidant function. MADS-box genes play an important role in the regulation of fruit development in angiosperms. OBJECTIVE: To understand the regulatory role of the MADS-box family, a total of 80 MADS-box genes were identified and analyzed. METHODS: The MADS-box genes in the black raspberry genome were analyzed using bioinformatics methods. Through an analysis of the promoter elements, the possible functions of different members of the family were predicted. The spatiotemporal expression patterns of members of the MADS-box family during black raspberry fruit development and ripening were systematically analyzed. RESULTS: The genes were classified into type I (Mα: 33; Mβ: 6; Mγ: 10) and type II (MIKC *: 2; MIKCC: 29) genes. We also obtained a complete overview of the RoMADS-box gene family through phylogenetic, gene structure, conserved motif, and cis element analyses. The relative expression analysis showed different expression patterns, and most RoMADS-box genes were more highly expressed in fruit than in other tissues of black raspberry. CONCLUSIONS: This finding indicates that the MADS-box gene family is involved in the regulation of fruit ripening processes in black raspberry.

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