Comparison Of Transcriptional Responses Research Articles

Dynamic Transcriptional Landscape of Mycobacterium smegmatis under Cold Stress.

Bacterial adaptation to cold stress requires wide transcriptional reprogramming. However, the knowledge of molecular mechanisms underlying the cold stress response of mycobacteria is limited. We conducted comparative transcriptomic analysis of Mycobacterium smegmatis subjected to cold shock. The growth of M. smegmatis cultivated at 37 °C was arrested just after exposure to cold (acclimation phase) but later (by 24 h) was resumed at a much slower rate (adaptation phase). Transcriptomic analyses revealed distinct gene expression patterns corresponding to the two phases. During the acclimation phase, differential expression was observed for genes associated with cell wall remodeling, starvation response, and osmotic pressure stress, in parallel with global changes in the expression of transcription factors and the downregulation of ribosomal genes, suggesting an energy-saving strategy to support survival. At the adaptation phase, the expression profiles were recovered, indicating restoration of the processes repressed earlier. Comparison of transcriptional responses in M. smegmatis with those in other bacteria revealed unique adaptation strategies developed by mycobacteria. Our findings shed light on the molecular mechanisms underlying M. smegmatis survival under cold stress. Further research should clarify whether the discovered transcriptional mechanisms exist in other mycobacterial species, including pathogenic Mycobacterium tuberculosis, which could be important for transmission control.

Abstract 2101: Comparison of transcriptional response to phorbol ester, bryostatin 1, and bryostatin analogue in LNCaP and U937 cells provides insight into their differential mechanism.

Abstract Bryostatin 1 (bryo 1) is a promising cancer chemotherapeutic agent with a unique mechanism of action. Whereas bryo 1 binds to and activates protein kinase C (PKC) like the phorbol esters, it paradoxically antagonizes most phorbol ester responses. Previously, we compared the changes in transcription in response to the phorbol ester phorbol 12-myristate 13-acetate (PMA), to bryo 1, and to the synthetic bryo 1 derivative Merle 23 in the human cancer cell lines LNCaP and U937. Bryo1 failed to induce a typical phorbol ester biological response in either cell line, whereas the bryo 1 analog Merle 23 resembled PMA in the U937 cells and bryo 1 in the LNCaP cells. In both cell lines, bryo 1 differed from PMA in inducing a shorter duration of the transcriptional responses for a panel of PKC-regulated genes as quantitated by qPCR. Merle 23, in contrast, induced a pattern very similar to that of PMA. Here, we analyzed by microarray the genome wide transcriptional changes in LNCaP and U937 cells treated with maximally effective doses of PMA, bryo 1 and Merle 23 for 6 and 8 hours, respectively. Several thousand genes were significantly up- or down-regulated by PMA (3131 and 3206), bryo 1 (1569 and 2454) and Merle 23 (3533 and 3207) compared to control in LNCaP and U937 cells, respectively. As seen previously for selected genes, the magnitude of the changes was much greater for LNCaP cells than for U937 cells. The great majority of the genes followed a pattern in which bryo 1 induced changes similar to PMA but to a significantly smaller extent (3096 and 1610 genes significantly different in LNCaP and U937 cells), whereas Merle 23 was very similar to PMA (only 230 and 30 genes different between them). A detailed qPCR analysis (dose and time courses) of representative outlier genes revealed that the shorter duration of bryo 1 induced response was responsible for the differences between bryo 1 and PMA effect in all cases. The dose response experiments did not reveal a difference in bryo 1 potency linked to any specific pattern of response. Analysis of transcription factors revealed overrepresentation of the same families of transcription factors (13 in the LNCaP cells; 12 in the U937 cells) among the genes differentially regulated by PMA and bryo 1. These included AP2F, E2F, EGRF, KLF, NRF1, SP1F. However, the target genes of the transcription factor families were largely different between the two cell lines. The analysis of 45 signaling pathways using reporter assays identified significant changes in 7 pathways induced both by PMA and bryo 1 at 6 hours. While the analysis of the microarray data is ongoing, we conclude that early turn-off of the induced responses by bryo 1 is the central feature accounting for its difference from PMA in its transcriptional response. Understanding the basis for this transiency of response may reveal a more general strategy for inhibition of PKC pathways. Citation Format: Noemi Kedei, Aleksandra M. Michalowski, Mark E. Petersen, Gary E. Keck, Peter M. Blumberg. Comparison of transcriptional response to phorbol ester, bryostatin 1, and bryostatin analogue in LNCaP and U937 cells provides insight into their differential mechanism. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2101. doi:10.1158/1538-7445.AM2013-2101

Abstract 3815: Comparison of transcriptional response to phorbol ester, bryostatin 1, and bryostatin analogues in LNCaP and U937 cancer cell lines provides insight into their differential mechanism of action

Abstract Bryostatin 1 has attracted great interest as a cancer chemotherapeutic agent with a unique mechanism of action. Whereas bryostatin 1 binds to and activates protein kinase C (PKC) like the phorbol esters, it paradoxically antagonizes many but not all phorbol ester responses. We wish to understand its mechanism(s) of action and how the newly emerging synthetic bryostatin analogs functionally resemble or differ from bryostatin 1. Previously, we have compared patterns of biological response to bryostatin 1, the phorbol ester phorbol 12-myristate 13-acetate (PMA), and the synthetic bryostatin 1 derivative Merle 23 in two human cancer cell lines, LNCaP and U937. Bryostatin 1 fails to induce a typical phorbol ester biological response in either cell line, whereas the bryostatin analog Merle 23 resembles PMA in the U937 cells and bryostatin 1 in the LNCaP cells. Here, we have compared patterns of transcriptional response to bryostatin 1, PMA, and Merle 23 in the same two human cancer cell lines. We examined by qPCR the transcriptional response as a function of dose and time for a series of genes highly regulated downstream of protein kinase C. In both cell lines, bryostatin 1 differed from phorbol ester primarily in having a shorter duration of transcriptional modulation. In LNCaP cells bryostatin 1 induced the majority of the genes similarly to PMA at 2 hours but to much lower levels at 6, 12, and 24 hrs. In U937 cells the bryostatin 1 induced response was similar to that of PMA at 2 hrs but progressively less than that of PMA at 8 hrs and 24 hrs. This was not due to bryostatin 1 instability, since bryostatin 1 suppressed the PMA response at these later times. A notable difference between the two cell lines was in the extent of transcriptional response to PMA, which was much greater in the LNCaP cells than in the U937 cells. In both cell lines Merle 23 induced a pattern of transcription largely like that of PMA rather than bryostatin 1 although with a modest reduction in expression at later times (12 and 24 hrs) in the LNCaP cells. We thus conclude that the difference in biological response of the two cell lines to Merle 23 most likely does not reflect an underlying difference in mechanism but rather reflects the greater absolute magnitude of the differences in response in the LNCaP cells compared to the U937 cells. For a series of bryostatins and synthetic analogues which ranged from bryostatin 1-like to phorbol ester-like in activity on the U937 cells for proliferation and differentiation, the duration of transcriptional response correlated with their pattern of biological activity, suggesting that this may provide a useful endpoint for structure activity analysis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3815. doi:1538-7445.AM2012-3815

Functional Associations by Response Overlap (FARO), a Functional Genomics Approach Matching Gene Expression Phenotypes

The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental factors including treatments, mutations and pathogen infections. Similarly, drugs may be discovered by the relationship between the transcript profiles effectuated or impacted by a candidate drug and by the target disease. The integration of such data enables systems biology to predict the interplay between experimental factors affecting a biological system. Unfortunately, direct comparisons of gene expression profiles obtained in independent, publicly available microarray experiments are typically compromised by substantial, experiment-specific biases. Here we suggest a novel yet conceptually simple approach for deriving ‘Functional Association(s) by Response Overlap’ (FARO) between microarray gene expression studies. The transcriptional response is defined by the set of differentially expressed genes independent from the magnitude or direction of the change. This approach overcomes the limited comparability between studies that is typical for methods that rely on correlation in gene expression. We apply FARO to a compendium of 242 diverse Arabidopsis microarray experimental factors, including phyto-hormones, stresses and pathogens, growth conditions/stages, tissue types and mutants. We also use FARO to confirm and further delineate the functions of Arabidopsis MAP kinase 4 in disease and stress responses. Furthermore, we find that a large, well-defined set of genes responds in opposing directions to different stress conditions and predict the effects of different stress combinations. This demonstrates the usefulness of our approach for exploiting public microarray data to derive biologically meaningful associations between experimental factors. Finally, our results indicate that FARO is more powerful in associating mutants in common pathways than existing methods such as co-expression analysis.

Comparison of transcriptional responses in liver tissue and primary hepatocyte cell cultures after exposure to hexahydro-1, 3, 5-trinitro-1, 3, 5-triazine

BackgroundCell culture systems are useful in studying toxicological effects of chemicals such as Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), however little is known as to how accurately isolated cells reflect responses of intact organs. In this work, we compare transcriptional responses in livers of Sprague-Dawley rats and primary hepatocyte cells after exposure to RDX to determine how faithfully the in vitro model system reflects in vivo responses.ResultsExpression patterns were found to be markedly different between liver tissue and primary cell cultures before exposure to RDX. Liver gene expression was enriched in processes important in toxicology such as metabolism of amino acids, lipids, aromatic compounds, and drugs when compared to cells. Transcriptional responses in cells exposed to 7.5, 15, or 30 mg/L RDX for 24 and 48 hours were different from those of livers isolated from rats 24 hours after exposure to 12, 24, or 48 mg/Kg RDX. Most of the differentially expressed genes identified across conditions and treatments could be attributed to differences between cells and tissue. Some similarity was observed in RDX effects on gene expression between tissue and cells, but also significant differences that appear to reflect the state of the cell or tissue examined.ConclusionLiver tissue and primary cells express different suites of genes that suggest they have fundamental differences in their cell physiology. Expression effects related to RDX exposure in cells reflected a fraction of liver responses indicating that care must be taken in extrapolating from primary cells to whole animal organ toxicity effects.

Use of oligonucleotide arrays to analyze drug toxicity.

The advent of oligonucleotide arrays allows the simultaneous analysis of the expression of thousands of genes. This powerful technology, highly dependent on advanced analysis tools, can transform the level of information currently available on the mechanisms underlying drug-related toxicity. It is now possible to analyze the global transcriptional response to a drug and determine the global pathways associated with the effects of this agent. This analysis can be performed on samples from patients that developed a toxic effect, on cells exposed to the toxic agent, and in animal models of toxicity. Especially useful is the comparison of transcriptional responses in animals susceptible to drug-induced disease with those of genetically modified animals that are resistant to this effect. This analytic strategy allows the delineation of specific mechanisms relevant and specific to drug-induced toxicity and thus might lead to novel therapeutic interventions in these toxic reactions.