RegulonDB v12.0: a comprehensive resource of transcriptional regulation in E. coli K-12.

RegulonDB is a database that contains the most comprehensive corpus of knowledge of the regulation of transcription initiation of Escherichia coli K-12, including data from both classical molecular biology and high-throughput methodologies. Here, we describe biological advances since our last NAR paper of 2019. We explain the changes to satisfy FAIR requirements. We also present a full reconstruction of the RegulonDB computational infrastructure, which has significantly improved data storage, retrieval and accessibility and thus supports a more intuitive and user-friendly experience. The integration of graphical tools provides clear visual representations of genetic regulation data, facilitating data interpretation and knowledge integration. RegulonDB version 12.0 can be accessed at https://regulondb.ccg.unam.mx.

Microaerobic degradation of crude oil and long chain alkanes by a new Rhodococcus strain from Gulf of Mexico.

Bacterial degradation of crude oil is a promising strategy for reducing the concentration of hydrocarbons in contaminated environments. In the first part of this study, we report the enrichment of two bacterial consortia from deep sediments of the Gulf of Mexico with crude oil as the sole carbon and energy source. We conducted a comparative analysis of the bacterial community in the original sediment, assessing its diversity, and compared it to the enrichment observed after exposure to crude oil in defined cultures. The consortium exhibiting the highest hydrocarbon degradation was predominantly enriched with Rhodococcus (75%). Bacterial community analysis revealed the presence of other hydrocarbonoclastic members in both consortia. In the second part, we report the isolation of the strain Rhodococcus sp. GOMB7 with crude oil as a unique carbon source under microaerobic conditions and its characterization. This strain demonstrated the ability to degrade long-chain alkanes, including eicosane, tetracosane, and octacosane. We named this new strain Rhodococcus qingshengii GOMB7. Genome analysis revealed the presence of several genes related to aromatic compound degradation, such as benA, benB, benC, catA, catB, and catC; and five alkB genes related to alkane degradation. Although members of the genus Rhodococcus are well known for their great metabolic versatility, including the aerobic degradation of recalcitrant organic compounds such as petroleum hydrocarbons, this is the first report of a novel strain of Rhodococcus capable of degrading long-chain alkanes under microaerobic conditions. The potential of R. qingshengii GOMB7 for applications in bioreactors or controlled systems with low oxygen levels offers an energy-efficient approach for treating crude oil-contaminated water and sediments.

Cyanate Assimilation by the Alkaliphilic Cyanide-Degrading Bacterium Pseudomonas pseudoalcaligenes CECT5344: Mutational Analysis of the cyn Gene Cluster.

The alkaliphilic bacterium Pseudomonas pseudoalcaligenes CECT5344 can grow with cyanate, cyanide, or cyanide-containing industrial residues as the sole nitrogen source, but the assimilation of cyanide and cyanate takes place through independent pathways. Therefore, cyanide degradation involves a chemical reaction between cyanide and oxaloacetate to form a nitrile that is hydrolyzed to ammonium by the nitrilase NitC, whereas cyanate assimilation requires a cyanase that catalyzes cyanate decomposition to ammonium and carbon dioxide. The P. pseudoalcaligenes CECT5344 cynFABDS gene cluster codes for the putative transcriptional regulator CynF, the ABC-type cyanate transporter CynABD, and the cyanase CynS. In this study, transcriptional analysis revealed that the structural cynABDS genes constitute a single transcriptional unit, which was induced by cyanate and repressed by ammonium. Mutational characterization of the cyn genes indicated that CynF was essential for cynABDS gene expression and that nitrate/nitrite transporters may be involved in cyanate uptake, in addition to the CynABD transport system. Biodegradation of hazardous jewelry wastewater containing high amounts of cyanide and metals was achieved in a batch reactor operating at an alkaline pH after chemical treatment with hydrogen peroxide to oxidize cyanide to cyanate.

Pseudomonas pseudoalcaligenes CECT5344, a cyanide-degrading bacterium with by-product (polyhydroxyalkanoates) formation capacity.

BACKGROUND: Cyanide is one of the most toxic chemicals produced by anthropogenic activities like mining and jewelry industries, which generate wastewater residues with high concentrations of this compound. Pseudomonas pseudoalcaligenes CECT5344 is a model microorganism to be used in detoxification of industrial wastewaters containing not only free cyanide (CN(-)) but also cyano-derivatives, such as cyanate, nitriles and metal-cyanide complexes. Previous in silico analyses suggested the existence of genes putatively involved in metabolism of short chain length (scl-) and medium chain length (mcl-) polyhydroxyalkanoates (PHAs) located in three different clusters in the genome of this bacterium. PHAs are polyesters considered as an alternative of petroleum-based plastics. Strategies to optimize the bioremediation process in terms of reducing the cost of the production medium are required. RESULTS: In this work, a biological treatment of the jewelry industry cyanide-rich wastewater coupled to PHAs production as by-product has been considered. The functionality of the pha genes from P. pseudoalcaligenes CECT5344 has been demonstrated. Mutant strains defective in each proposed PHA synthases coding genes (Mpha(-), deleted in putative mcl-PHA synthases; Spha(-), deleted in the putative scl-PHA synthase) were generated. The accumulation and monomer composition of scl- or mcl-PHAs in wild type and mutant strains were confirmed by gas chromatography-mass spectrometry (GC-MS). The production of PHAs as by-product while degrading cyanide from the jewelry industry wastewater was analyzed in batch reactor in each strain. The wild type and the mutant strains grew at similar rates when using octanoate as the carbon source and cyanide as the sole nitrogen source. When cyanide was depleted from the medium, both scl-PHAs and mcl-PHAs were detected in the wild-type strain, whereas scl-PHAs or mcl-PHAs were accumulated in Mpha(-) and Spha(-), respectively. The scl-PHAs were identified as homopolymers of 3-hydroxybutyrate and the mcl-PHAs were composed of 3-hydroxyoctanoate and 3-hydroxyhexanoate monomers. CONCLUSIONS: These results demonstrated, as proof of concept, that talented strains such as P. pseudoalcaligenes might be applied in bioremediation of industrial residues containing cyanide, while concomitantly generate by-products like polyhydroxyalkanoates. A customized optimization of the target bioremediation process is required to gain benefits of this type of approaches.

Flexible gold standards for transcription factor regulatory interactions in Escherichia coli K-12: architecture of evidence types.

Post-genomic implementations have expanded the experimental strategies to identify elements involved in the regulation of transcription initiation. Here, we present for the first time a detailed analysis of the sources of knowledge supporting the collection of transcriptional regulatory interactions (RIs) of Escherichia coli K-12. An RI groups the transcription factor, its effect (positive or negative) and the regulated target, a promoter, a gene or transcription unit. We improved the evidence codes so that specific methods are incorporated and classified into independent groups. On this basis we updated the computation of confidence levels, weak, strong, or confirmed, for the collection of RIs. These updates enabled us to map the RI set to the current collection of HT TF-binding datasets from ChIP-seq, ChIP-exo, gSELEX and DAP-seq in RegulonDB, enriching in this way the evidence of close to one-quarter (1329) of RIs from the current total 5446 RIs. Based on the new computational capabilities of our improved annotation of evidence sources, we can now analyze the internal architecture of evidence, their categories (experimental, classical, HT, computational), and confidence levels. This is how we know that the joint contribution of HT and computational methods increase the overall fraction of reliable RIs (the sum of confirmed and strong evidence) from 49% to 71%. Thus, the current collection has 3912 reliable RIs, with 2718 or 70% of them with classical evidence which can be used to benchmark novel HT methods. Users can selectively exclude the method they want to benchmark, or keep for instance only the confirmed interactions. The recovery of regulatory sites in RegulonDB by the different HT methods ranges between 33% by ChIP-exo to 76% by ChIP-seq although as discussed, many potential confounding factors limit their interpretation. The collection of improvements reported here provides a solid foundation to incorporate new methods and data, and to further integrate the diverse sources of knowledge of the different components of the transcriptional regulatory network. There is no other genomic database that offers this comprehensive high-quality architecture of knowledge supporting a corpus of transcriptional regulatory interactions.

A Gold Standard for Transcription Factor Regulatory Interactions in Escherichia coli K-12: Architecture of Evidence Types.

Post-genomic implementations have expanded the experimental strategies to identify elements involved in the regulation of transcription initiation. As new methodologies emerge, a natural step is to compare their results with those from established methodologies, such as the classic methods of molecular biology used to characterize transcription factor binding sites, promoters, or transcription units. In the case of Escherichia coli K-12, the best-studied microorganism, for the last 30 years we have continuously gathered such knowledge from original scientific publications, and have organized it in two databases, RegulonDB and EcoCyc. Furthermore, since RegulonDB version 11.0 (1), we offer comprehensive datasets of binding sites from chromatin immunoprecipitation combined with sequencing (ChIP-seq), ChIP combined with exonuclease digestion and next-generation sequencing (ChIP-exo), genomic SELEX screening (gSELEX), and DNA affinity purification sequencing (DAP-seq) HT technologies, as well as additional datasets for transcription start sites, transcription units and RNA sequencing (RNA-seq) expression profiles. Here, we present for the first time an analysis of the sources of knowledge supporting the collection of transcriptional regulatory interactions (RIs) of E. coli K-12. An RI is formed by the transcription factor, its positive or negative effect on a promoter, a gene or transcription unit. We improved the evidence codes so that the specific methods are described, and we classified them into seven independent groups. This is the basis for our updated computation of confidence levels, weak, strong, or confirmed, for the collection of RIs. We compare the confidence levels of the RI collection before and after adding HT evidence illustrating how knowledge will change as more HT data and methods appear in the future. Users can generate subsets filtering out the method they want to benchmark and avoid circularity, or keep for instance only the confirmed interactions. The comparison of different HT methods with the available datasets indicate that ChIP-seq recovers the highest fraction (>70%) of binding sites present in RegulonDB followed by gSELEX, DAP-seq and ChIP-exo. There is no other genomic database that offers this comprehensive high-quality anatomy of evidence supporting a corpus of transcriptional regulatory interactions.

The EcoCyc Database (2023).

EcoCyc is a bioinformatics database available online at EcoCyc.org that describes the genome and the biochemical machinery of Escherichia coli K-12 MG1655. The long-term goal of the project is to describe the complete molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists and for biologists who work with related microorganisms. The database includes information pages on each E. coli gene product, metabolite, reaction, operon, and metabolic pathway. The database also includes information on the regulation of gene expression, E. coli gene essentiality, and nutrient conditions that do or do not support the growth of E. coli. The website and downloadable software contain tools for the analysis of high-throughput data sets. In addition, a steady-state metabolic flux model is generated from each new version of EcoCyc and can be executed online. The model can predict metabolic flux rates, nutrient uptake rates, and growth rates for different gene knockouts and nutrient conditions. Data generated from a whole-cell model that is parameterized from the latest data on EcoCyc are also available. This review outlines the data content of EcoCyc and of the procedures by which this content is generated.

Sensory Systems and Transcriptional Regulation in Escherichia coli.

In free-living bacteria, the ability to regulate gene expression is at the core of adapting and interacting with the environment. For these systems to have a logic, a signal must trigger a genetic change that helps the cell to deal with what implies its presence in the environment; briefly, the response is expected to include a feedback to the signal. Thus, it makes sense to think of genetic sensory mechanisms of gene regulation. Escherichia coli K-12 is the bacterium model for which the largest number of regulatory systems and its sensing capabilities have been studied in detail at the molecular level. In this special issue focused on biomolecular sensing systems, we offer an overview of the transcriptional regulatory corpus of knowledge for E. coli that has been gathered in our database, RegulonDB, from the perspective of sensing regulatory systems. Thus, we start with the beginning of the information flux, which is the signal's chemical or physical elements detected by the cell as changes in the environment; these signals are internally transduced to transcription factors and alter their conformation. Signals transduced to effectors bind allosterically to transcription factors, and this defines the dominant sensing mechanism in E. coli. We offer an updated list of the repertoire of known allosteric effectors, as well as a list of the currently known different mechanisms of this sensing capability. Our previous definition of elementary genetic sensory-response units, GENSOR units for short, that integrate signals, transport, gene regulation, and the biochemical response of the regulated gene products of a given transcriptional factor fit perfectly with the purpose of this overview. We summarize the functional heterogeneity of their response, based on our updated collection of GENSORs, and we use them to identify the expected feedback as part of their response. Finally, we address the question of multiple sensing in the regulatory network of E. coli. This overview introduces the architecture of sensing and regulation of native components in E.coli K-12, which might be a source of inspiration to bioengineering applications.

RegulonDB 11.0: Comprehensive high-throughput datasets on transcriptional regulation in Escherichia coli K-12.

Genomics has set the basis for a variety of methodologies that produce high-throughput datasets identifying the different players that define gene regulation, particularly regulation of transcription initiation and operon organization. These datasets are available in public repositories, such as the Gene Expression Omnibus, or ArrayExpress. However, accessing and navigating such a wealth of data is not straightforward. No resource currently exists that offers all available high and low-throughput data on transcriptional regulation in Escherichia coli K-12 to easily use both as whole datasets, or as individual interactions and regulatory elements. RegulonDB (https://regulondb.ccg.unam.mx) began gathering high-throughput dataset collections in 2009, starting with transcription start sites, then adding ChIP-seq and gSELEX in 2012, with up to 99 different experimental high-throughput datasets available in 2019. In this paper we present a radical upgrade to more than 2000 high-throughput datasets, processed to facilitate their comparison, introducing up-to-date collections of transcription termination sites, transcription units, as well as transcription factor binding interactions derived from ChIP-seq, ChIP-exo, gSELEX and DAP-seq experiments, besides expression profiles derived from RNA-seq experiments. For ChIP-seq experiments we offer both the data as presented by the authors, as well as data uniformly processed in-house, enhancing their comparability, as well as the traceability of the methods and reproducibility of the results. Furthermore, we have expanded the tools available for browsing and visualization across and within datasets. We include comparisons against previously existing knowledge in RegulonDB from classic experiments, a nucleotide-resolution genome viewer, and an interface that enables users to browse datasets by querying their metadata. A particular effort was made to automatically extract detailed experimental growth conditions by implementing an assisted curation strategy applying Natural language processing and machine learning. We provide summaries with the total number of interactions found in each experiment, as well as tools to identify common results among different experiments. This is a long-awaited resource to make use of such wealth of knowledge and advance our understanding of the biology of the model bacterium E. coli K-12.

Transcriptome Analysis Reveals Cr(VI) Adaptation Mechanisms in Klebsiella sp. Strain AqSCr.

Klebsiella sp. strain AqSCr, isolated from Cr(VI)-polluted groundwater, reduces Cr(VI) both aerobically and anaerobically and resists up 34 mM Cr(VI); this resistance is independent of the ChrA efflux transporter. In this study, we report the whole genome sequence and the transcriptional profile by RNA-Seq of strain AqSCr under Cr(VI)-adapted conditions and found 255 upregulated and 240 downregulated genes compared to controls without Cr(VI) supplementation. Genes differentially transcribed were mostly associated with oxidative stress response, DNA repair and replication, sulfur starvation response, envelope-osmotic stress response, fatty acid (FA) metabolism, ribosomal subunits, and energy metabolism. Among them, genes not previously associated with chromium resistance, for example, cybB, encoding a putative superoxide oxidase (SOO), gltA2, encoding an alternative citrate synthase, and des, encoding a FA desaturase, were upregulated. The sodA gene encoding a manganese superoxide dismutase was upregulated in the presence of Cr(VI), whereas sodB encoding an iron superoxide dismutase was downregulated. Cr(VI) resistance mechanisms in strain AqSCr seem to be orchestrated by the alternative sigma factors fecl, rpoE, and rpoS (all of them upregulated). Membrane lipid analysis of the Cr(IV)-adapted strain showed a lower proportion of unsaturated lipids with respect to the control, which we hypothesized could result from unsaturated lipid peroxidation followed by degradation, together with de novo synthesis mediated by the upregulated FA desaturase-encoding gene, des. This report helps to elucidate both Cr(VI) toxicity targets and global bacterial response to Cr(VI).

Role of the Dihydrodipicolinate Synthase DapA1 on Iron Homeostasis During Cyanide Assimilation by the Alkaliphilic Bacterium Pseudomonas pseudoalcaligenes CECT5344.

Cyanide is a toxic compound widely used in mining and jewelry industries, as well as in the synthesis of many different chemicals. Cyanide toxicity derives from its high affinity for metals, which causes inhibition of relevant metalloenzymes. However, some cyanide-degrading microorganisms like the alkaliphilic bacterium Pseudomonas pseudoalcaligenes CECT5344 may detoxify hazardous industrial wastewaters that contain elevated cyanide and metal concentrations. Considering that iron availability is strongly reduced in the presence of cyanide, mechanisms for iron homeostasis should be required for cyanide biodegradation. Previous omic studies revealed that in the presence of a cyanide-containing jewelry residue the strain CECT5344 overproduced the dihydrodipicolinate synthase DapA1, a protein involved in lysine metabolism that also participates in the synthesis of dipicolinates, which are excellent metal chelators. In this work, a dapA1 - mutant of P. pseudoalcaligenes CECT5344 has been generated and characterized. This mutant showed reduced growth and cyanide consumption in media with the cyanide-containing wastewater. Intracellular levels of metals like iron, copper and zinc were increased in the dapA1 - mutant, especially in cells grown with the jewelry residue. In addition, a differential quantitative proteomic analysis by LC-MS/MS was carried out between the wild-type and the dapA1 - mutant strains in media with jewelry residue. The mutation in the dapA1 gene altered the expression of several proteins related to urea cycle and metabolism of arginine and other amino acids. Additionally, the dapA1 - mutant showed increased levels of the global nitrogen regulator PII and the glutamine synthetase. This proteomic study has also highlighted that the DapA1 protein is relevant for cyanide resistance, oxidative stress and iron homeostasis response, which is mediated by the ferric uptake regulator Fur. DapA1 is required to produce dipicolinates that could act as iron chelators, conferring protection against oxidative stress and allowing the regeneration of Fe-S centers to reactivate cyanide-damaged metalloproteins.

Putative small RNAs controlling detoxification of industrial cyanide-containing wastewaters by Pseudomonas pseudoalcaligenes CECT5344.

The alkaliphilic bacterium Pseudomonas pseudoalcaligenes CECT5344 uses free cyanide and several metal-cyanide complexes as the sole nitrogen source and tolerates high concentrations of metals like copper, zinc and iron, which are present in the jewelry wastewaters. To understand deeply the regulatory mechanisms involved in the transcriptional regulation of cyanide-containing wastewaters detoxification by P. pseudoalcaligenes CECT5344, RNA-Seq has been performed from cells cultured with a cyanide-containing jewelry wastewater, sodium cyanide or ammonium chloride as the sole nitrogen source. Small RNAs (sRNAs) that may have potential regulatory functions under cyanotrophic conditions were identified. In total 20 sRNAs were identified to be differentially expressed when compared the jewelry residue versus ammonium as nitrogen source, 16 of which could be amplified successfully by RT-PCR. As predicted targets of these 16 sRNAs were several components of the nit1C gene cluster encoding the nitrilase NitC essential for cyanide assimilation, the cioAB gene cluster that codes for the cyanide-insensitive cytochrome bd-type terminal oxidase, the medium length-polyhydroxyalkanoates (ml-PHAs) gene cluster, and gene clusters related with a global nitrogen limitation response like those coding for glutamine synthase and urease. Other targets were non-clustered genes (or their products) involved in metal resistance and iron acquisition, such as metal extrusion systems and the ferric uptake regulatory (Fur) protein, and a GntR-like regulatory family member probably involved in the regulation of the cyanide assimilation process in the strain CECT5344. Induction of genes targeted by sRNAs in the jewelry residue was demonstrated by qRT-PCR.

Acetate biostimulation as an effective treatment for cleaning up alkaline soil highly contaminated with Cr(VI).

Stimulation of microbial reduction of Cr(VI) to the less toxic and less soluble Cr(III) through electron donor addition has been regarded as a promising approach for the remediation of chromium-contaminated soil and groundwater sites. However, each site presents different challenges; local physicochemical characteristics and indigenous microbial communities influence the effectiveness of the biostimulation processes. Here, we show microcosm assays stimulation of microbial reduction of Cr(VI) in highly alkaline and saline soil samples from a long-term contaminated site in Guanajuato, Mexico. Acetate was effective promoting anaerobic microbial reduction of 15 mM of Cr(VI) in 25 days accompanied by an increase in pH from 9 to 10. Our analyses showed the presence of Halomonas, Herbaspirillum, Nesterenkonia/Arthrobacter, and Bacillus species in the soil sample collected. Moreover, from biostimulated soil samples, it was possible to isolate Halomonas spp. strains able to grow at 32 mM of Cr(VI). Additionally, we found that polluted groundwater has bacterial species different to those found in soil samples with the ability to resist and reduce chromate using acetate and yeast extract as electron donors.

[Implementation of a clinical prediction tool in renal transplant recipients]. / Aplicación de una herramienta de predicción pronóstica en receptores de trasplante renal.

BACKGROUND: Kasiske developed a tool for predicting the risk of 5-year graft loss. We analyzed our results using this model. METHODS: 109 deceased donor kidney transplants were included. 5-year probability of graft survival was calculated during transplantation, seven days after transplantation and 1-year after transplantation. Z-test and ROC curves were used for proportion differences and discrimination ability. RESULTS: Mean age of donor and recipient was 33.7 and 33.9 years, respectively. 59.6% died due to trauma. Mean of years on dialysis was 3.7. 22.9% of patients had delayed graft function (DGF). Calculated 5-year probability of graft survival during transplantation time was 74.1%; 7 days after transplantation, 74.9%; and one year after transplantation, 76.4%. 5-year death censored graft survival was 64.9%. There were no differences between death-censored graft survival and calculated probabilities (Z-test), with a C-statistic value of 0.54 ± 0.6 (95%CI 0.42-0.65, p = 0.5) and 0.51 ± 0.6 (0.39-0.63, 95% CI, p = 0. 7) for transplant time and seven days after. C-statistic value 1-year after transplantation was 0.68 ± 0.8 (95%CI 0.52-0.84, p = 0.02). CONCLUSION: Only calculated 5-year graft survival one year after transplantation had modest prediction ability.

Introducción: Kasiske desarrolló una herramienta para predecir el riesgo de pérdida del injerto a cinco años. Se analizaron los resultados utilizando este modelo. Métodos: se incluyeron 109 pacientes trasplantados de donantes fallecidos. La probabilidad de sobrevida del injerto a cinco años fue calculada al momento del trasplante, a los siete días y al año. La prueba Z y las curvas ROC fueron utilizadas para diferencias de proporción y capacidad de discriminación. Resultados: la media de edad del donador y del receptor fue 33.7 y 33.9 años, respectivamente. El 59.6% falleció de trauma. La media de años en diálisis fue de 3.7. El 22.9% tuvo retraso en la función del injerto. La probabilidad de sobrevida a cinco años del injerto en el momento del trasplante fue de 74.1%; siete días después fue de 74.9% y al año 76.4%. La sobrevida actuarial a cinco años del injerto fue 64.9%. No hubo diferencias entre la sobrevida del injerto y las probabilidades calculadas (prueba Z) con valor estadístico C de 0.54 ± 0.6 (intervalo de confianza al 95% [IC 95%] 0.42-0.65, p = 0.5) y 0.51 ± 0.6 (IC 95% 0.39-0.63, p = 0.7) para el tiempo de trasplante y al séptimo día. El valor estadístico C después del trasplante a un año fue de 0.68 ± 0.8 (IC 95% 0.52-0.84, p = 0.02). Conclusión: existió una predicción modesta al calcular la sobrevida del injerto a cinco años a un año posterior al trasplante.