Interaction networks of Escherichia coli replication proteins under different bacterial growth conditions.

In this work we analyzed protein-protein interactions (PPIs) formed by E. coli replication proteins under three disparate bacterial growth conditions. The chosen conditions corresponded to fast exponential growth, slow exponential growth and growth cessation at the stationary phase. We performed affinity purification coupled with mass spectrometry (AP-MS) of chromosomally expressed proteins (DnaA, DnaB, Hda, SeqA, DiaA, DnaG, HolD, NrdB), tagged with sequential peptide affinity (SPA) tag. Composition of protein complexes was characterized using MaxQuant software. To filter out unspecific interactions, we employed double negative control system and we proposed qualitative and quantitative data analysis strategies that can facilitate hits identification in other AP-MS datasets. Our motivation to undertake this task was still insufficient understanding of molecular mechanisms coupling DNA replication to cellular growth. Previous works suggested that such control mechanisms could involve physical interactions of replication factors with metabolic or cell envelope proteins. However, the dynamic replication protein interaction network (PIN) obtained in this study can be used to characterize links between DNA replication and various cellular processes in other contexts.

Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform.

BACKGROUND: Thermography is a popular tool to assess plant water-use behavior, as plant temperature is influenced by transpiration rate, and is commonly used in field experiments to detect plant water deficit. Its application in indoor automated phenotyping platforms is still limited and mainly focuses on differences in plant temperature between genotypes or treatments, instead of estimating stomatal conductance or transpiration rate. In this study, the transferability of commonly used thermography analysis protocols from the field to greenhouse phenotyping platforms was evaluated. In addition, the added value of combining thermal infrared (TIR) with hyperspectral imaging to monitor drought effects on plant transpiration rate (E) was evaluated. RESULTS: The sensitivity of commonly used TIR indices to detect drought-induced and genotypic differences in water status was investigated in eight maize inbred lines in the automated phenotyping platform PHENOVISION. Indices that normalized plant temperature for vapor pressure deficit and/or air temperature at the time of imaging were most sensitive to drought and could detect genotypic differences in the plants' water-use behavior. However, these indices were not strongly correlated to stomatal conductance and E. The canopy temperature depression index, the crop water stress index and the simplified stomatal conductance index were more suitable to monitor these traits, and were consequently used to develop empirical E prediction models by combining them with hyperspectral indices and/or environmental variables. Different modeling strategies were evaluated, including single index-based, machine learning and mechanistic models. Model comparison showed that combining multiple TIR indices in a random forest model can improve E prediction accuracy, and that the contribution of the hyperspectral data is limited when multiple indices are used. However, the empirical models trained on one genotype were not transferable to all eight inbred lines. CONCLUSION: Overall, this study demonstrates that existing TIR indices can be used to monitor drought stress and develop E prediction models in an indoor setup, as long as the indices normalize plant temperature for ambient air temperature or relative humidity.

Ubiquitin Proteasome System Role in Diabetes-Induced Cardiomyopathy.

This study investigated modifications to the ubiquitin proteasome system (UPS) in a mouse model of type 2 diabetes mellitus (T2DM) and their relationship to heart complications. db/db mice heart tissues were compared with WT mice tissues using RNA sequencing, qRT-PCR, and protein analysis to identify cardiac UPS modifications associated with diabetes. The findings unveiled a distinctive gene profile in the hearts of db/db mice with decreased levels of nppb mRNA and increased levels of Myh7, indicating potential cardiac dysfunction. The mRNA levels of USP18 (deubiquitinating enzyme), PSMB8, and PSMB9 (proteasome ß-subunits) were down-regulated in db/db mice, while the mRNA levels of RNF167 (E3 ligase) were increased. Corresponding LMP2 and LMP7 proteins were down-regulated in db/db mice, and RNF167 was elevated in Adult diabetic mice. The reduced expression of LMP2 and LMP7, along with increased RNF167 expression, may contribute to the future cardiac deterioration commonly observed in diabetes. This study enhances our understanding of UPS imbalances in the hearts of diabetic mice and raises questions about the interplay between the UPS and other cellular processes, such as autophagy. Further exploration in this area could provide valuable insights into the mechanisms underlying diabetic heart complications and potential therapeutic targets.

Predicting yield of individual field-grown rapeseed plants from rosette-stage leaf gene expression.

In the plant sciences, results of laboratory studies often do not translate well to the field. To help close this lab-field gap, we developed a strategy for studying the wiring of plant traits directly in the field, based on molecular profiling and phenotyping of individual plants. Here, we use this single-plant omics strategy on winter-type Brassica napus (rapeseed). We investigate to what extent early and late phenotypes of field-grown rapeseed plants can be predicted from their autumnal leaf gene expression, and find that autumnal leaf gene expression not only has substantial predictive power for autumnal leaf phenotypes but also for final yield phenotypes in spring. Many of the top predictor genes are linked to developmental processes known to occur in autumn in winter-type B. napus accessions, such as the juvenile-to-adult and vegetative-to-reproductive phase transitions, indicating that the yield potential of winter-type B. napus is influenced by autumnal development. Our results show that single-plant omics can be used to identify genes and processes influencing crop yield in the field.

What is a supercoiling-sensitive gene? Insights from topoisomerase I inhibition in the Gram-negative bacterium Dickeya dadantii.

DNA supercoiling is an essential mechanism of bacterial chromosome compaction, whose level is mainly regulated by topoisomerase I and DNA gyrase. Inhibiting either of these enzymes with antibiotics leads to global supercoiling modifications and subsequent changes in global gene expression. In previous studies, genes responding to DNA relaxation induced by DNA gyrase inhibition were categorised as 'supercoiling-sensitive'. Here, we studied the opposite variation of DNA supercoiling in the phytopathogen Dickeya dadantii using the non-marketed antibiotic seconeolitsine. We showed that the drug is active against topoisomerase I from this species, and analysed the first transcriptomic response of a Gram-negative bacterium to topoisomerase I inhibition. We find that the responding genes essentially differ from those observed after DNA relaxation, and further depend on the growth phase. We characterised these genes at the functional level, and also detected distinct patterns in terms of expression level, spatial and orientational organisation along the chromosome. Altogether, these results highlight that the supercoiling-sensitivity is a complex feature, which depends on the action of specific topoisomerases, on the physiological conditions, and on their genomic context. Based on previous in vitro expression data of several promoters, we propose a qualitative model of SC-dependent regulation that accounts for many of the contrasting transcriptomic features observed after DNA gyrase or topoisomerase I inhibition.

A Genome-Wide Evolutionary Simulation of the Transcription-Supercoiling Coupling.

DNA supercoiling, the level of under- or overwinding of the DNA polymer around itself, is widely recognized as an ancestral regulation mechanism of gene expression in bacteria. Higher levels of negative supercoiling facilitate the opening of the DNA double helix at gene promoters and thereby increase gene transcription rates. Different levels of supercoiling have been measured in bacteria exposed to different environments, leading to the hypothesis that variations in supercoiling could be a response to changes in the environment. Moreover, DNA transcription has been shown to generate local variations in the supercoiling level and, therefore, to impact the transcription rate of neighboring genes. In this work, we study the coupled dynamics of DNA supercoiling and transcription at the genome scale. We implement a genome-wide model of gene expression based on the transcription-supercoiling coupling. We show that, in this model, a simple change in global DNA supercoiling is sufficient to trigger differentiated responses in gene expression levels via the transcription-supercoiling coupling. Then, studying our model in the light of evolution, we demonstrate that this non-linear response to different environments, mediated by the transcription-supercoiling coupling, can serve as the basis for the evolution of specialized phenotypes.

Quantitative contribution of the spacer length in the supercoiling-sensitivity of bacterial promoters.

DNA supercoiling acts as a global transcriptional regulator in bacteria, but the promoter sequence or structural determinants controlling its effect remain unclear. It was previously proposed to modulate the torsional angle between the -10 and -35 hexamers, and thereby regulate the formation of the closed-complex depending on the length of the 'spacer' between them. Here, we develop a thermodynamic model of this notion based on DNA elasticity, providing quantitative and parameter-free predictions of the relative activation of promoters containing a short versus long spacer when the DNA supercoiling level is varied. The model is tested through an analysis of in vitro and in vivo expression assays of mutant promoters with variable spacer lengths, confirming its accuracy for spacers ranging from 15 to 19 nucleotides, except those of 16 nucleotides where other regulatory mechanisms likely overcome the effect of this specific step. An analysis at the whole-genome scale in Escherichia coli then demonstrates a significant effect of the spacer length on the genomic expression after transient or inheritable superhelical variations, validating the model's predictions. Altogether, this study shows an example of mechanical constraints associated to promoter binding by RNA Polymerase underpinning a basal and global regulatory mechanism.

Mapping the Complex Transcriptional Landscape of the Phytopathogenic Bacterium Dickeya dadantii.

Dickeya dadantii is a phytopathogenic bacterium that causes soft rot in a wide range of plant hosts worldwide and a model organism for studying virulence gene regulation. The present study provides a comprehensive and annotated transcriptomic map of D. dadantii obtained by a computational method combining five independent transcriptomic data sets: (i) paired-end RNA sequencing (RNA-seq) data for a precise reconstruction of the RNA landscape; (ii) DNA microarray data providing transcriptional responses to a broad variety of environmental conditions; (iii) long-read Nanopore native RNA-seq data for isoform-level transcriptome validation and determination of transcription termination sites; (iv) differential RNA sequencing (dRNA-seq) data for the precise mapping of transcription start sites; (v) in planta DNA microarray data for a comparison of gene expression profiles between in vitro experiments and the early stages of plant infection. Our results show that transcription units sometimes coincide with predicted operons but are generally longer, most of them comprising internal promoters and terminators that generate alternative transcripts of variable gene composition. We characterize the occurrence of transcriptional read-through at terminators, which might play a basal regulation role and explain the extent of transcription beyond the scale of operons. We finally highlight the presence of noncontiguous operons and excludons in the D. dadantii genome, novel genomic arrangements that might contribute to the basal coordination of transcription. The highlighted transcriptional organization may allow D. dadantii to finely adjust its gene expression program for a rapid adaptation to fast-changing environments. IMPORTANCE This is the first transcriptomic map of a Dickeya species. It may therefore significantly contribute to further progress in the field of phytopathogenicity. It is also one of the first reported applications of long-read Nanopore native RNA-seq in prokaryotes. Our findings yield insights into basal rules of coordination of transcription that might be valid for other bacteria and may raise interest in the field of microbiology in general. In particular, we demonstrate that gene expression is coordinated at the scale of transcription units rather than operons, which are larger functional genomic units capable of generating transcripts with variable gene composition for a fine-tuning of gene expression in response to environmental changes. In line with recent studies, our findings indicate that the canonical operon model is insufficient to explain the complexity of bacterial transcriptomes.

Spatial Regression Models for Field Trials: A Comparative Study and New Ideas.

Naturally occurring variability within a study region harbors valuable information on relationships between biological variables. Yet, spatial patterns within these study areas, e.g., in field trials, violate the assumption of independence of observations, setting particular challenges in terms of hypothesis testing, parameter estimation, feature selection, and model evaluation. We evaluate a number of spatial regression methods in a simulation study, including more realistic spatial effects than employed so far. Based on our results, we recommend generalized least squares (GLS) estimation for experimental as well as for observational setups and demonstrate how it can be incorporated into popular regression models for high-dimensional data such as regularized least squares. This new method is available in the BioConductor R-package pengls. Inclusion of a spatial error structure improves parameter estimation and predictive model performance in low-dimensional settings and also improves feature selection in high-dimensional settings by reducing "red-shift": the preferential selection of features with spatial structure. In addition, we argue that the absence of spatial autocorrelation (SAC) in the model residuals should not be taken as a sign of a good fit, since it may result from overfitting the spatial trend. Finally, we confirm our findings in a case study on the prediction of winter wheat yield based on multispectral measurements.

Carbon catabolite repression in pectin digestion by the phytopathogen Dickeya dadantii.

The catabolism of pectin from plant cell walls plays a crucial role in the virulence of the phytopathogen Dickeya dadantii. In particular, the timely expression of pel genes encoding major pectate lyases is essential to circumvent the plant defense systems and induce massive pectinolytic activity during the maceration phase. Previous studies identified the role of a positive feedback loop specific to the pectin-degradation pathway, whereas the precise signals controlling the dynamics of pectate lyase expression were unclear. Here, we show that the latter is controlled by a metabolic switch involving both glucose and pectin. We measured the HPLC concentration profiles of the key metabolites related to these two sources of carbon, cAMP and 2-keto-3-deoxygluconate, and developed a dynamic and quantitative model of the process integrating the associated regulators, cAMP receptor protein and KdgR. The model describes the regulatory events occurring at the promoters of two major pel genes, pelE and pelD. It highlights that their activity is controlled by a mechanism of carbon catabolite repression, which directly controls the virulence of D. dadantii. The model also shows that quantitative differences in the binding properties of common regulators at these two promoters resulted in a qualitatively different role of pelD and pelE in the metabolic switch, and also likely in conditions of infection, justifying their evolutionary conservation as separate genes in this species.

Role of the Discriminator Sequence in the Supercoiling Sensitivity of Bacterial Promoters.

DNA supercoiling acts as a global transcriptional regulator that contributes to the rapid transcriptional response of bacteria to many environmental changes. Although a large fraction of promoters from phylogenetically distant species respond to superhelical variations, the sequence or structural determinants of this behavior remain elusive. Here, we focus on the sequence of the "discriminator" element that was shown to modulate this response in several promoters. We develop a quantitative thermodynamic model of this regulatory effect, focusing on open complex formation during transcription initiation independently from promoter-specific regulatory proteins. We analyze previous and new expression data and show that the model predictions quantitatively match the in vitro and in vivo supercoiling response of selected promoters with mutated discriminator sequences. We then test the universality of this mechanism by a statistical analysis of promoter sequences from transcriptomes of phylogenetically distant bacteria under conditions of supercoiling variations (i) by gyrase inhibitors, (ii) by environmental stresses, or (iii) inherited in the longest-running evolution experiment. In all cases, we identify a robust and significant sequence signature in the discriminator region, suggesting that supercoiling-modulated promoter opening underpins a ubiquitous regulatory mechanism in the prokaryotic kingdom based on the fundamental mechanical properties of DNA and its basal interaction with RNA polymerase. IMPORTANCE In this study, we highlight the role of the discriminator as a global sensor of supercoiling variations and propose the first quantitative regulatory model of this principle, based on the specific step of promoter opening during transcription initiation. It defines the predictive rule by which DNA supercoiling quantitatively modulates the expression rate of bacterial promoters, depending on the G/C content of their discriminator and independently from promoter-specific regulatory proteins. This basal mechanism affects a wide range of species, which is tested by an extensive analysis of global high-throughput expression data. Altogether, ours results confirm and provide a quantitative framework for the long-proposed notion that the discriminator sequence is a significant determinant of promoter supercoiling sensitivity, underpinning the ubiquitous regulatory action of DNA supercoiling on the core transcriptional machinery, in particular in response to quick environmental changes.

Separation and quantification of 2-keto-3-deoxy-gluconate (KDG) a major metabolite in pectin and alginate degradation pathways.

A rapid and sensitive High Performance Liquid Chromatography (HPLC) method with photometric and fluorescence detection is developed for routine analysis of 2-Keto-3-deoxy-gluconate (KDG), a catabolite product of pectin and alginate. These polysaccharides are primary-based compounds for biofuel production and for generation of high-value-added products. HPLC is performed, after derivatization of the 2-oxo-acid groups of the metabolite with o-phenylenediamine (oPD), using a linear gradient of trifluoroacetic acid and acetonitrile. Quantification is accomplished with an internal standard method. The gradient is optimized to distinguish KDG from its close structural analogues such as 5-keto-4-deoxyuronate (DKI) and 2,5-diketo-3-deoxygluconate (DKII). The proposed method is simple, highly sensitive and accurate for time course analysis of pectin or alginate degradation.

The nucleoid-associated protein IHF acts as a 'transcriptional domainin' protein coordinating the bacterial virulence traits with global transcription.

Bacterial pathogenic growth requires a swift coordination of pathogenicity function with various kinds of environmental stress encountered in the course of host infection. Among the factors critical for bacterial adaptation are changes of DNA topology and binding effects of nucleoid-associated proteins transducing the environmental signals to the chromosome and coordinating the global transcriptional response to stress. In this study, we use the model phytopathogen Dickeya dadantii to analyse the organisation of transcription by the nucleoid-associated heterodimeric protein IHF. We inactivated the IHFα subunit of IHF thus precluding the IHFαß heterodimer formation and determined both phenotypic effects of ihfA mutation on D. dadantii virulence and the transcriptional response under various conditions of growth. We show that ihfA mutation reorganises the genomic expression by modulating the distribution of chromosomal DNA supercoils at different length scales, thus affecting many virulence genes involved in both symptomatic and asymptomatic phases of infection, including those required for pectin catabolism. Altogether, we propose that IHF heterodimer is a 'transcriptional domainin' protein, the lack of which impairs the spatiotemporal organisation of transcriptional stress-response domains harbouring various virulence traits, thus abrogating the pathogenicity of D. dadantii.

Using single-plant-omics in the field to link maize genes to functions and phenotypes.

Most of our current knowledge on plant molecular biology is based on experiments in controlled laboratory environments. However, translating this knowledge from the laboratory to the field is often not straightforward, in part because field growth conditions are very different from laboratory conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional laboratory-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.

TwisTranscripT: stochastic simulation of the transcription-supercoiling coupling.

SUMMARY: Transcription and DNA supercoiling are involved in a complex, dynamical and non-linear coupling that results from the basal interaction between DNA and RNA polymerase. We present the first software to simulate this coupling, applicable to a wide range of bacterial organisms. TwisTranscripT allows quantifying its contribution in global transcriptional regulation, and provides a mechanistic basis for the widely observed, evolutionarily conserved and currently unexplained co-regulation of adjacent operons that might play an important role in genome evolution. AVAILABILITY AND IMPLEMENTATION: TwisTranscripT is freely available at https://github.com/sammeyer2017/TwisTranscripT. It is implemented in Python3 and supported on MacOS X, Linux and Windows.

Coherent Domains of Transcription Coordinate Gene Expression During Bacterial Growth and Adaptation.

Recent studies strongly suggest that in bacteria, both the genomic pattern of DNA thermodynamic stability and the order of genes along the chromosomal origin-to-terminus axis are highly conserved and that this spatial organization plays a crucial role in coordinating genomic transcription. In this article, we explore the relationship between genomic sequence organization and transcription in the commensal bacterium Escherichia coli and the plant pathogen Dickeya. We argue that, while in E. coli the gradient of DNA thermodynamic stability and gene order along the origin-to-terminus axis represent major organizational features orchestrating temporal gene expression, the genomic sequence organization of Dickeya is more complex, demonstrating extended chromosomal domains of thermodynamically distinct DNA sequences eliciting specific transcriptional responses to various kinds of stress encountered during pathogenic growth. This feature of the Dickeya genome is likely an adaptation to the pathogenic lifestyle utilizing differences in genomic sequence organization for the selective expression of virulence traits. We propose that the coupling of DNA thermodynamic stability and genetic function provides a common organizational principle for the coordinated expression of genes during both normal and pathogenic bacterial growth.

DNA Supercoiling: an Ancestral Regulator of Gene Expression in Pathogenic Bacteria?

DNA supercoiling acts as a global and ancestral regulator of bacterial gene expression. In this review, we advocate that it plays a pivotal role in host-pathogen interactions by transducing environmental signals to the bacterial chromosome and coordinating its transcriptional response. We present available evidence that DNA supercoiling is modulated by environmental stress conditions relevant to the infection process according to ancestral mechanisms, in zoopathogens as well as phytopathogens. We review the results of transcriptomics studies obtained in widely distant bacterial species, showing that such structural transitions of the chromosome are associated to a complex transcriptional response affecting a large fraction of the genome. Mechanisms and computational models of the transcriptional regulation by DNA supercoiling are then discussed, involving both basal interactions of RNA Polymerase with promoter DNA, and more specific interactions with regulatory proteins. A final part is specifically focused on the regulation of virulence genes within pathogenicity islands of several pathogenic bacterial species.

APERO: a genome-wide approach for identifying bacterial small RNAs from RNA-Seq data.

Small non-coding RNAs (sRNAs) regulate numerous cellular processes in all domains of life. Several approaches have been developed to identify them from RNA-seq data, which are efficient for eukaryotic sRNAs but remain inaccurate for the longer and highly structured bacterial sRNAs. We present APERO, a new algorithm to detect small transcripts from paired-end bacterial RNA-seq data. In contrast to previous approaches that start from the read coverage distribution, APERO analyzes boundaries of individual sequenced fragments to infer the 5' and 3' ends of all transcripts. Since sRNAs are about the same size as individual fragments (50-350 nucleotides), this algorithm provides a significantly higher accuracy and robustness, e.g., with respect to spontaneous internal breaking sites. To demonstrate this improvement, we develop a comparative assessment on datasets from Escherichia coli and Salmonella enterica, based on experimentally validated sRNAs. We also identify the small transcript repertoire of Dickeya dadantii including putative intergenic RNAs, 5' UTR or 3' UTR-derived RNA products and antisense RNAs. Comparisons to annotations as well as RACE-PCR experimental data confirm the precision of the detected transcripts. Altogether, APERO outperforms all existing methods in terms of sRNA detection and boundary precision, which is crucial for comprehensive genome annotations. It is freely available as an open source R package on https://github.com/Simon-Leonard/APERO.

Bacterial genome architecture shapes global transcriptional regulation by DNA supercoiling.

DNA supercoiling acts as a global transcriptional regulator in bacteria, that plays an important role in adapting their expression programme to environmental changes, but for which no quantitative or even qualitative regulatory model is available. Here, we focus on spatial supercoiling heterogeneities caused by the transcription process itself, which strongly contribute to this regulation mode. We propose a new mechanistic modeling of the transcription-supercoiling dynamical coupling along a genome, which allows simulating and quantitatively reproducing in vitro and in vivo transcription assays, and highlights the role of genes' local orientation in their supercoiling sensitivity. Consistently with predictions, we show that chromosomal relaxation artificially induced by gyrase inhibitors selectively activates convergent genes in several enterobacteria, while conversely, an increase in DNA supercoiling naturally selected in a long-term evolution experiment with Escherichia coli favours divergent genes. Simulations show that these global expression responses to changes in DNA supercoiling result from fundamental mechanical constraints imposed by transcription, independently from more specific regulation of each promoter. These constraints underpin a significant and predictable contribution to the complex rules by which bacteria use DNA supercoiling as a global but fine-tuned transcriptional regulator.

ThreaDNA: predicting DNA mechanics' contribution to sequence selectivity of proteins along whole genomes.

Motivation: Many DNA-binding proteins recognize their target sequences indirectly, by sensing DNA's response to mechanical distortion. ThreaDNA estimates this response based on high-resolution structures of the protein-DNA complex of interest. Implementing an efficient nanoscale modeling of DNA deformations involving essentially no adjustable parameters, it returns the profile of deformation energy along whole genomes, at base-pair resolution, within minutes on usual laptop/desktop computers. Our predictions can also be easily combined with estimations of direct selectivity through a generalized form of position-weight-matrices. The formalism of ThreaDNA is accessible to a wide audience. Results: We demonstrate the importance of indirect readout for the nucleosome as well as the bacterial regulators Fis and CRP. Combined with the direct contribution provided by usual sequence motifs, it significantly improves the prediction of sequence selectivity, and allows quantifying the two distinct physical mechanisms underlying it. Availability and implementation: Python software available at bioinfo.insa-lyon.fr, natively executable on Linux/MacOS systems with a user-friendly graphical interface. Galaxy webserver version available. Contact: sam.meyer@insa-lyon.fr. Supplementary information: Supplementary data are available at Bioinformatics online.