Delineating the effect of host environmental signals on a fully virulent strain of Bacillus anthracis using an integrated transcriptomics and proteomics approach

Panda, Gurudutta; Tanwer, Pooja; Sengupta, Shantanu; Santos, Vítor A. P. Martins dos; Bhatnagar, Rakesh

doi:10.1016/j.jprot.2013.12.018

Cited by 8 publications

(10 citation statements)

References 120 publications

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“…The lack of correlation between transcriptome and proteome data also implies that changes of the transcriptome mostly lead to minimal or transient changes of the proteome that are not manifested over longer time intervals. Earlier studies on growth phase-dependent changes in RNA and protein levels have noted such weak correlation between the data sets [5, 7, 28] and raised the question of to what extent is the bacterial proteome regulated at the level of transcription [6].…”

Section: Discussionmentioning

confidence: 99%

“…Transcriptomic approaches have been used to study the changes between the growth phases [2, 3]. A combined transcriptomic and proteomic approach has the advantage of providing deeper insights into the molecular changes underlying bacterial growth adaptation [4–7]. Generally, we expected the information flow from DNA to RNA to correlate with the RNA to protein conversion, i.e., changes in the transcriptome are predicted to lead to corresponding changes in the proteome and metabolome.…”

Section: Introductionmentioning

confidence: 99%

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Comparative analyses of the variation of the transcriptome and proteome of Rhodobacter sphaeroides throughout growth

et al. 2019

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Background In natural environments, bacteria must frequently cope with extremely scarce nutrients. Most studies focus on bacterial growth in nutrient replete conditions, while less is known about the stationary phase. Here, we are interested in global gene expression throughout all growth phases, including the adjustment to deep stationary phase. Results We monitored both the transcriptome and the proteome in cultures of the alphaproteobacterium Rhodobacter sphaeroides , beginning with the transition to stationary phase and at different points of the stationary phase and finally during exit from stationary phase (outgrowth) following dilution with fresh medium. Correlation between the transcriptomic and proteomic changes was very low throughout the growth phases. Surprisingly, even in deep stationary phase, the abundance of many proteins continued to adjust, while the transcriptome analysis revealed fewer adjustments. This pattern was reversed during the first 90 min of outgrowth, although this depended upon the duration of the stationary phase. We provide a detailed analysis of proteomic changes based on the clustering of orthologous groups (COGs), and compare these with the transcriptome. Conclusions The low correlation between transcriptome and proteome supports the view that post-transcriptional processes play a major role in the adaptation to growth conditions. Our data revealed that many proteins with functions in transcription, energy production and conversion and the metabolism and transport of amino acids, carbohydrates, lipids, and secondary metabolites continually increased in deep stationary phase. Based on these findings, we conclude that the bacterium responds to sudden changes in environmental conditions by a radical and rapid reprogramming of the transcriptome in the first 90 min, while the proteome changes were modest. In response to gradually deteriorating conditions, however, the transcriptome remains mostly at a steady state while the bacterium continues to adjust its proteome. Even long after the population has entered stationary phase, cells are still actively adjusting their proteomes. Electronic supplementary material The online version of this article (10.1186/s12864-019-5749-3) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparative analyses of the variation of the transcriptome and proteome of Rhodobacter sphaeroides throughout growth

et al. 2019

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“…MS/MS spectra were acquired for the 25 most abundant precursor ions, with a total accumulation of 3000 shots. For MS/MS precursor selection, the minimum signal/noise ratio (S/N) filter was set at 25 with an exclusion list for CHCA matrix and keratin peaks 50 .…”

Section: Methodsmentioning

confidence: 99%

Plasma proteomic analysis of stable coronary artery disease indicates impairment of reverse cholesterol pathway

Tanwar

Bhardwaj

et al. 2016

Sci Rep

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Coronary artery disease (CAD) is one of the largest causes of death worldwide yet the traditional risk factors, although useful in identifying people at high risk, lack the desired predictive accuracy. Techniques like quantitative plasma proteomics holds immense potential to identify newer markers and this study (conducted in three phases) was aimed to identify differentially expressed proteins in stable CAD patients. In the first (discovery) phase, plasma from CAD cases (angiographically proven) and controls were subjected to iTRAQ based proteomic analysis. Proteins found to be differentially expressed were then validated in the second and third (verification and validation) phases in larger number of (n = 546) samples. After multivariate logistic regression adjusting for confounding factors (age, diet, etc.), four proteins involved in the reverse cholesterol pathway (Apo A1, ApoA4, Apo C1 and albumin) along with diabetes and hypertension were found to be significantly associated with CAD and could account for approximately 88% of the cases as revealed by ROC analysis. The maximum odds ratio was found to be 6.70 for albumin (p < 0.0001), followed by Apo AI (5.07, p < 0.0001), Apo CI (4.03, p = 0.001), and Apo AIV (2.63, p = 0.003). Down-regulation of apolipoproteins and albumin implicates the impairment of reverse cholesterol pathway in CAD.

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“…As such, two omics studies of the same type performed under different growth conditions can produce different results, making it difficult to draw solid conclusions about the targetome (5,6). To alleviate these problems, multiple omics datasets can be integrated to reduce false positives and elucidate direct targets and the true core responses of the network (7,8). Nevertheless, the use of omics studies for this comprehensive characterization of global response pathways is only beginning to be realized (3,9,10).…”

Section: Introductionmentioning

confidence: 99%

Integrative FourD omics approach profiles the target network of the carbon storage regulatory system

et al. 2017

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Multi-target regulators represent a largely untapped area for metabolic engineering and anti-bacterial development. These regulators are complex to characterize because they often act at multiple levels, affecting proteins, transcripts and metabolites. Therefore, single omics experiments cannot profile their underlying targets and mechanisms. In this work, we used an Integrative FourD omics approach (INFO) that consists of collecting and analyzing systems data throughout multiple time points, using multiple genetic backgrounds, and multiple omics approaches (transcriptomics, proteomics and high throughput sequencing crosslinking immunoprecipitation) to evaluate simultaneous changes in gene expression after imposing an environmental stress that accentuates the regulatory features of a network. Using this approach, we profiled the targets and potential regulatory mechanisms of a global regulatory system, the well-studied carbon storage regulatory (Csr) system of Escherichia coli, which is widespread among bacteria. Using 126 sets of proteomics and transcriptomics data, we identified 136 potential direct CsrA targets, including 50 novel ones, categorized their behaviors into distinct regulatory patterns, and performed in vivo fluorescence-based follow up experiments. The results of this work validate 17 novel mRNAs as authentic direct CsrA targets and demonstrate a generalizable strategy to integrate multiple lines of omics data to identify a core pool of regulator targets.

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Delineating the effect of host environmental signals on a fully virulent strain of Bacillus anthracis using an integrated transcriptomics and proteomics approach

Cited by 8 publications

References 120 publications

Comparative analyses of the variation of the transcriptome and proteome of Rhodobacter sphaeroides throughout growth

Comparative analyses of the variation of the transcriptome and proteome of Rhodobacter sphaeroides throughout growth

Plasma proteomic analysis of stable coronary artery disease indicates impairment of reverse cholesterol pathway

Integrative FourD omics approach profiles the target network of the carbon storage regulatory system

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