Background: Glucose is the preferred carbon and energy source for Escherichia coli. A complex regulatory network coordinates gene expression, transport and enzyme activities in response to the presence of this sugar. To determine the extent of the cellular response to glucose, we applied an approach combining global transcriptome and regulatory network analyses. Results: Transcriptome data from isogenic wild type and crp ^- strains grown in Luria-Bertani medium (LB) or LB + 4 g/L glucose (LB+G) were analyzed to identify differentially transcribed genes. We detected 180 and 200 genes displaying increased and reduced relative transcript levels in the presence of glucose, respectively. The observed expression pattern in LB was consistent with a gluconeogenic metabolic state including active transport and interconversion of small molecules and macromolecules, induction of protease-encoding genes and a partial heat shock response. In LB+G, catabolic repression was detected for transport and metabolic interconversion activities. We also detected an increased capacity for de novo synthesis of nucleotides, amino acids and proteins. Cluster analysis of a subset of genes revealed that CRP mediates catabolite repression for most of the genes displaying reduced transcript levels in LB+G, whereas Fis participates in the upregulation of genes under this condition. An analysis of the regulatory network, in terms of topological functional units, revealed 8 interconnected modules which again exposed the importance of Fis and CRP as directly responsible for the coordinated response of the cell. This effect was also seen with other not extensively connected transcription factors such as FruR and PdhR, which showed a consistent response considering media composition. Conclusion: This work allowed the identification of eight interconnected regulatory network modules that includes CRP, Fis and other transcriptional factors that respond directly or indirectly to the presence of glucose. In most cases, each of these modules includes genes encoding physiologically related functions, thus indicating a connection between regulatory network topology and related cellular functions involved in nutrient sensing and metabolism.

Marine sediments constitute the world’s most substantial long-term carbon repository. The microorganisms dwelling in these sediments mediate the transformation of fixed oceanic carbon, but their contribution to the carbon cycle is not fully understood. Previous culture-independent investigations into sedimentary microorganisms have underscored the significance of carbohydrates in the carbon cycle. In this study, we employ a metagenomic methodology to investigate the distribution and abundance of carbohydrate-active enzymes (CAZymes) in 37 marine sediments sites. These sediments exhibit varying oxygen availability and were isolated in diverse regions worldwide. Our comparative analysis is based on the metabolic potential for oxygen utilisation, derived from genes present in both oxic and anoxic environments. We found that extracellular CAZyme modules targeting the degradation of plant and algal detritus, necromass, and host glycans were abundant across all metagenomic samples. The analysis of these results indicates that the oxic/anoxic conditions not only influence the taxonomic composition of the microbial communities, but also affect the occurrence of CAZyme modules involved in the transformation of necromass, algae and plant detritus. To gain insight into the sediment microbial taxa, we reconstructed metagenome assembled genomes (MAG) and examined the presence of primary extracellular carbohydrate active enzyme (CAZyme) modules. Our findings reveal that the primary CAZyme modules and the CAZyme gene clusters discovered in our metagenomes were prevalent in the Bacteroidia, Gammaproteobacteria, and Alphaproteobacteria classes. We compared those MAGs to organisms from the same taxonomic classes found in soil, and we found that they were similar in its CAZyme repertoire, but the soil MAG contained a more abundant and diverse CAZyme content. Furthermore, the data indicate that abundant classes in our metagenomic samples, namely Alphaproteobacteria, Bacteroidia and Gammaproteobacteria, play a pivotal role in carbohydrate transformation within the initial few metres of the sediments.

Background: The regulation of gene expression at the transcriptional level is a fundamental process in prokaryotes. Among the different kind of mechanisms modulating gene transcription, the one based on DNA binding transcription factors, is the most extensively studied and the results, for a great number of model organisms, have been compiled making it possible the in silico construction of their corresponding transcriptional regulatory networks and the analysis of the biological relationships of the components of these intricate networks, that allows to elucidate the significant aspects of their organization and evolution. Results: We present a thorough review of each regulatory element that constitutes the transcriptional regulatory network of Bacillus subtilis. For facilitating the discussion, we organized the network in topological modules. Our study highlight the importance of σ factors, some of them acting as master regulators which characterize modules by inter- or intra-connecting them and play a key role in the cascades that define relevant cellular processes in this organism. We discussed that some particular functions were distributed in more than one module and that some modules contained more than one related function. We confirm that the presence of paralogous proteins confers advantages to B. subtilis to adapt and select strategies to successfully face the extreme and changing environmental conditions in which it lives. Conclusions: The intricate organization is the product of a non-random network evolution that primarily follows a hierarchical organization based on the presence of transcription and σ factor, which is reflected in the connections that exist within and between modules.

Background: After the initial outbreak in China (December 2019), the World Health Organization declared COVID-19 a pandemic on March 11^th, 2020. This paper aims to describe the first 2 years of the pandemic in Mexico.Design and methods: This is a population-based longitudinal study. We analyzed data from the national COVID-19 registry to describe the evolution of the pandemic in terms of the number of confirmed cases, hospitalizations, deaths and reported symptoms in relation to health policies and circulating variants. We also carried out logistic regression to investigate the major risk factors for disease severity.Results: From March 2020 to March 2022, the coronavirus disease 2019 (COVID-19) pandemic in Mexico underwent four epidemic waves. Out of 5,702,143 confirmed cases, 680,063 were hospitalized (11.9%), and 324,436 (5.7%) died. Even if there was no difference in susceptibility by gender, males had a higher risk of death (CFP: 7.3 vs. 4.2%) and hospital admission risk (HP: 14.4 vs. 9.5%). Severity increased with age. With respect to younger ages (0–17 years), the 60+ years or older group reached adjusted odds ratios of 9.63 in the case of admission and 53.05 (95% CI: 27.94–118.62) in the case of death. The presence of any comorbidity more than doubled the odds ratio, with hypertension-diabetes as the riskiest combination. While the wave peaks increased over time, the odds ratios for developing severe disease (waves 2, 3, and 4 to wave 1) decreased to 0.15 (95% CI: 0.12–0.18) in the fourth wave.Conclusion: The health policy promoted by the Mexican government decreased hospitalizations and deaths, particularly among older adults with the highest risk of admission and death. Comorbidities augment the risk of developing severe illness, which is shown to rise by double in the Mexican population, particularly for those reported with hypertension-diabetes. Factors such as the decrease in the severity of the SARS-CoV2 variants, changes in symptomatology, and advances in the management of patients, vaccination, and treatments influenced the decrease in mortality and hospitalizations.

In this study, we analyzed the sequences of SARS-CoV-2 isolates of the Delta variant in Mexico, which has completely replaced other previously circulating variants in the country due to its transmission advantage. Among all the Delta sublineages that were detected, 81.5 % were classified as AY.20, AY.26, and AY.100. According to publicly available data, these only reached a world prevalence of less than 1%, suggesting a possible Mexican origin. The signature mutations of these sublineages are described herein, and phylogenetic analyses and haplotype networks are used to track their spread across the country. Other frequently detected sublineages include AY.3, AY.62, AY.103, and AY.113. Over time, the main sublineages showed different geographical distributions, with AY.20 predominant in Central Mexico, AY.26 in the North, and AY.100 in the Northwest and South/Southeast. This work describes the circulation, from May to November 2021, of the primary sublineages of the Delta variant associated with the third wave of the COVID-19 pandemic in Mexico and highlights the importance of SARS-CoV-2 genomic surveillance for the timely identification of emerging variants that may impact public health.

The first step of anaerobic benzoate degradation is the formation of benzoyl-coenzyme A by benzoate-coenzyme A ligase (BCL). The anaerobic route is steered by benzoyl-CoA reductase, which promotes benzoyl-CoA breakdown, which is subsequently oxidized. In certain bacteria at low oxygen conditions, the aerobic metabolism of monoaromatic hydrocarbons occurs through the degradation Box pathway. These pathways have undergone experimental scrutiny in Alphaproteobacteria and Betaproteobacteria and have also been explored bioinformatically in representative Betaproteobacteria. However, there is a gap in our knowledge regarding the distribution of the benzoyl-CoA pathway and the evolutionary forces propelling its adaptation beyond that of representative bacteria. To address these questions, we used bioinformatic procedures to identify the BCLs and the lower pathways that transform benzoyl-CoA. These procedures included the identification of conserved motifs. As a result, we identified two motifs exclusive to BCLs, describing some of the catalytic properties of this enzyme. These motifs helped to discern BCLs from other aryl-CoA ligases effectively. The predicted BCLs and the enzymes of lower pathways were used as genomic markers for identifying aerobic, anaerobic, or hybrid catabolism, which we found widely distributed in Betaproteobacteria. Despite these enhancements, our approach failed to distinguish orthologs from a small cluster of paralogs exhibiting all the specified features to predict an ortholog. Nonetheless, the conducted phylogenetic analysis and the properties identified in the genomic context aided in formulating hypotheses about how this redundancy contributes to refining the catabolic strategy employed by these bacteria to degrade the substrates.