Omicron-BA.1 Dispersion Rates in Mexico Varied According to the Regional Epidemic Patterns and the Diversity of Local Delta Subvariants.

PURPOSE: The Omicron subvariant BA.1 of SARS-CoV-2 was first detected in November 2021 and quickly spread worldwide, displacing the Delta variant. In this work, a characterization of the spread of this variant in Mexico is presented. METHODS: The time to fixation of BA.1, the diversity of Delta sublineages, the population density, and the level of virus circulation during the inter-wave interval were determined to analyze differences in BA.1 spread. RESULTS: BA.1 began spreading during the first week of December 2021 and became dominant in the next three weeks, causing the fourth COVID-19 epidemiological surge in Mexico. Unlike previous variants, BA.1 did not exhibit a geographically distinct circulation pattern. However, a regional difference in the speed of the replacement of the Delta variant was observed. CONCLUSIONS: Viral diversity and the relative abundance of the virus in a particular area around the time of the introduction of a new lineage seem to have influenced the spread dynamics, in addition to population density. Nonetheless, if there is a significant difference in the fitness of the variants, or if the time allowed for the competition is sufficiently long, it seems the fitter virus will eventually become dominant, as observed in the eventual dominance of the BA.1.x variant in Mexico.

The benzoyl-CoA pathway serves as a genomic marker to identify the oxygen requirements in the degradation of aromatic hydrocarbons.

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.

Dominance of Three Sublineages of the SARS-CoV-2 Delta Variant in Mexico.

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 Alpha Variant (B.1.1.7) of SARS-CoV-2 Failed to Become Dominant in Mexico.

During the coronavirus disease 2019 (COVID-19) pandemic, the emergence and rapid increase of the B.1.1.7 (Alpha) lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first identified in the United Kingdom in September 2020, was well documented in different areas of the world and became a global public health concern because of its increased transmissibility. The B.1.1.7 lineage was first detected in Mexico during December 2020, showing a slow progressive increase in its circulation frequency, which reached its maximum in May 2021 but never became predominant. In this work, we analyzed the patterns of diversity and distribution of this lineage in Mexico using phylogenetic and haplotype network analyses. Despite the reported increase in transmissibility of the B.1.1.7 lineage, in most Mexican states, it did not displace cocirculating lineages, such as B.1.1.519, which dominated the country from February to May 2021. Our results show that the states with the highest prevalence of B.1.1.7 were those at the Mexico-U.S. border. An apparent pattern of dispersion of this lineage from the northern states of Mexico toward the center or the southeast was observed in the largest transmission chains, indicating possible independent introduction events from the United States. However, other entry points cannot be excluded, as shown by multiple introduction events. Local transmission led to a few successful haplotypes with a localized distribution and specific mutations indicating sustained community transmission. IMPORTANCE The emergence and rapid increase of the B.1.1.7 (Alpha) lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the world were due to its increased transmissibility. However, it did not displace cocirculating lineages in most of Mexico, particularly B.1.1.519, which dominated the country from February to May 2021. In this work, we analyzed the distribution of B.1.1.7 in Mexico using phylogenetic and haplotype network analyses. Our results show that the states with the highest prevalence of B.1.1.7 (around 30%) were those at the Mexico-U.S. border, which also exhibited the highest lineage diversity, indicating possible introduction events from the United States. Also, several haplotypes were identified with a localized distribution and specific mutations, indicating that sustained community transmission occurred in the country.

Two-year follow-up of the COVID-19 pandemic in Mexico.

Background: After the initial outbreak in China (December 2019), the World Health Organization declared COVID-19 a pandemic on March 11th, 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.

Video bioinformatics analysis of human pluripotent stem cell morphology, quality, and cellular dynamics.

StemCellQC is a video bioinformatics software tool for the quantitative analysis of human pluripotent stem cell (hPSC) colonies. Our objective was to use StemCellQC to evaluate and compare various experimental culture conditions, cell lines, and treatments and to demonstrate its applicability to PSC problems. Seven key features were identified that provided useful information on PSC morphology, dynamic behavior, and viability. Colony attachment was better on laminin-521 than on Matrigel and Geltrex. Growth rates were similar on each matrix when data were normalized. The brightness/area ratio feature showed greater cell death in colonies grown on Matrigel and Geltrex than on laminin-521 further contributing to an overall greater yield of cells on laminin-521. Four different PSC culture media performed similarly; however, one medium produced batch-to-batch variation in colony morphology and dynamic features. Two embryonic and one induced pluripotent stem cell line showed significant differences in morphology, growth rates, motility, and death rates. Cells from the same vial that became phenotypically different in culture showed measurable differences in morphology, brightness, and motility. Likewise, differentiating and undifferentiated colonies varied in growth rate, intensity, and motility. Three pluripotent cell lines treated with a low concentration of cinnamaldehyde, a chemical used in consumer products, showed adverse effects and differed in their sensitivity to treatment. Our data demonstrate various applications of StemCellQC which could be used in basic and translational research, toxicological and drug testing, and clinical facilities engaged in stem cell therapy.

Definition of the Metagenomic Profile of Ocean Water Samples From the Gulf of Mexico Based on Comparison With Reference Samples From Sites Worldwide.

Computational and statistical analysis of shotgun metagenomes can predict gene abundance and is helpful for elucidating the functional and taxonomic compositions of environmental samples. Gene products are compared against physicochemical conditions or perturbations to shed light on the functions performed by the microbial community of an environmental sample; however, this information is not always available. The present study proposes a method for inferring the metabolic potential of metagenome samples by constructing a reference based on determining the probability distribution of the counts of each enzyme annotated. To test the methodology, we used marine water samples distributed worldwide as references. Then, the references were utilized to compare the annotated enzymes of two different water samples extracted from the Gulf of Mexico (GoM) to distinguish those enzymes with atypical behavior. The enzymes whose annotation counts presented frequencies significantly different from those of the reference were used to perform metabolic reconstruction, which naturally identified pathways. We found that several of the enzymes were involved in the biodegradation of petroleum, which is consistent with the impact of human hydrocarbon extraction activity and its ubiquitous presence in the GoM. The examination of other reconstructed pathways revealed significant enzymes indicating the presence of microbial communities characterizing each ocean depth and ocean cycle, providing a fingerprint of each sampled site.

Chemical Elements in Electronic Cigarette Solvents and Aerosols Inhibit Mitochondrial Reductases and Induce Oxidative Stress.

INTRODUCTION: Chemical elements and their toxicity were evaluated in electronic cigarette (EC) solvents, fluids, and aerosols. AIMS AND METHODS: Element identification and quantification in propylene glycol (PG), glycerin (G), refill fluids before and after use, and aerosols was done using inductively coupled plasma optical emission spectrometry. Cytotoxicity and oxidative stress were evaluated using in vitro assays. RESULTS: Seven elements were present in PG, G, and popular refill fluids, and they transferred to aerosols made with ECs. Selenium was in all products (0.125-0.292 mg/L), while arsenic, aluminum, and tin were frequently in solvent and refill fluid samples at lower concentrations. Iron, chromium, copper, nickel, zinc, and lead were only detected in fluid after EC use, indicating they came from heated atomizers. Elements transferred most efficiently to aerosols made with second-/third-generation ECs. Of the elements in fluid, selenium and arsenic were the most cytotoxic to human bronchial epithelial cells (BEAS-2B) and pulmonary fibroblasts in the 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide assay. Selenium increased superoxide production in mitochondria and nucleoli and elevated selenoprotein H in nucleoli of BEAS-2B cells at concentrations found in EC aerosols (10 nM or 0.002 mg/L). CONCLUSIONS: Elements in EC aerosols came from both e-fluids and atomizing units. Within second-/third-generation products, transfer became more efficient as power increased. In vitro responses occurred at concentrations of selenium found in some EC aerosols. Human exposure to chemical elements in ECs could be reduced by regulating (decreasing) allowable EC power and by improving the purity of PG and G. IMPLICATIONS: PG, G, refill fluids, and e-fluids contained potentially toxic chemical elements that transferred to aerosols. Transfer was more efficient in second- and third-generation EC products and increased as power increased. Selenium and arsenic were the most cytotoxic of the elements tested in the 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide assay. Selenium tetrachloride-induced oxidative stress in BEAS-2B cells, but not in human pulmonary fibroblasts. All fluids contained selenium above the concentration that induced oxidative stress in human bronchial epithelial cells. Selenium increased superoxide in mitochondria and nucleoli and increased selenoprotein H, a redox responsive DNA-binding protein that is upregulated by superoxide and an indicator of nucleolar stress. EC users are exposed to elements in aerosols, which may with chronic exposure contribute to diseases associated with oxidative stress.

Metagenomic Profiling and Microbial Metabolic Potential of Perdido Fold Belt (NW) and Campeche Knolls (SE) in the Gulf of Mexico.

The Gulf of Mexico (GoM) is a particular environment that is continuously exposed to hydrocarbon compounds that may influence the microbial community composition. We carried out a metagenomic assessment of the bacterial community to get an overall view of this geographical zone. We analyzed both taxonomic and metabolic markers profiles to explain how the indigenous GoM microorganims participate in the biogeochemical cycling. Two geographically distant regions in the GoM, one in the north-west (NW) and one in the south-east (SE) of the GoM were analyzed and showed differences in their microbial composition and metabolic potential. These differences provide evidence the delicate equilibrium that sustains microbial communities and biogeochemical cycles. Based on the taxonomy and gene groups, the NW are more oxic sediments than SE ones, which have anaerobic conditions. Both water and sediments show the expected sulfur, nitrogen, and hydrocarbon metabolism genes, with particularly high diversity of the hydrocarbon-degrading ones. Accordingly, many of the assigned genera were associated with hydrocarbon degradation processes, Nitrospira and Sva0081 were the most abundant in sediments, while Vibrio, Alteromonas, and Alcanivorax were mostly detected in water samples. This basal-state analysis presents the GoM as a potential source of aerobic and anaerobic hydrocarbon degradation genes important for the ecological dynamics of hydrocarbons and the potential use for water and sediment bioremediation processes.

Prediction of Medical Concepts in Electronic Health Records: Similar Patient Analysis.

BACKGROUND: Medicine 2.0-the adoption of Web 2.0 technologies such as social networks in health care-creates the need for apps that can find other patients with similar experiences and health conditions based on a patient's electronic health record (EHR). Concurrently, there is an increasing number of longitudinal EHR data sets with rich information, which are essential to fulfill this need. OBJECTIVE: This study aimed to evaluate the hypothesis that we can leverage similar EHRs to predict possible future medical concepts (eg, disorders) from a patient's EHR. METHODS: We represented patients' EHRs using time-based prefixes and suffixes, where each prefix or suffix is a set of medical concepts from a medical ontology. We compared the prefixes of other patients in the collection with the state of the current patient using various interpatient distance measures. The set of similar prefixes yields a set of suffixes, which we used to determine probable future concepts for the current patient's EHR. RESULTS: We evaluated our methods on the Multiparameter Intelligent Monitoring in Intensive Care II data set of patients, where we achieved precision up to 56.1% and recall up to 69.5%. For a limited set of clinically interesting concepts, specifically a set of procedures, we found that 86.9% (353/406) of the true-positives are clinically useful, that is, these procedures were actually performed later on the patient, and only 4.7% (19/406) of true-positives were completely irrelevant. CONCLUSIONS: These initial results indicate that predicting patients' future medical concepts is feasible. Effectively predicting medical concepts can have several applications, such as managing resources in a hospital.

Prediction of protein architectures involved in the signaling-pathway initiating sporulation in Firmicutes.

OBJECTIVES: Like many other proteins, those belonging to the signal transduction cascade initiating sporulation (Spo0 pathway) have conserved protein domains (Capra and Laub in Annu Rev Microbiol 66:325-47, 2012). Improvements in bioinformatics applications to discover proteins involved in the initiation of the sporulating cascade in newly sequenced genomes is an important task that requires rigorous comparative genomic methods and manual curation to identify endospore-forming bacteria. This note aims to present a collection of predicted proteins involved in the Spo0 pathway found in the proteomes of fully sequenced and manually curated endospore-forming Firmicutes species. This collection may serve as a guide to conduct future experiments in endospore formers in genomic and metagenomic projects. DATA DESCRIPTION: Similar to the report of Davidson et al. (PLoS Genet 14:1-33, 2018), we used Pfam profiles (El-Gebali et al. in Nucleic Acids Res 47:D427-32, 2019) defining each protein and the genomic context surrounding the query gene to predict probable orthologs of the Spo0 pathway in Firmicutes. We present in this note a collection of 325 Firmicutes species organized by phylogenetic class and classified as spore formers, non-spore formers or unknown spore phenotype based on published literature, for which we predicted probable orthologs defining the signal transduction pathway initiating sporulation.

Reactant pairs and reaction organization patterns produced by a new rule-based approach.

OBJECTIVES: Improvements in bioinformatics applications for the enzyme identification of biochemical reactions, enzyme classifications, mining for specific inhibitors and pathfinding require the accurate computational detection of reaction similarity. We provide a set of substrate-product pairs, clustered by reactions that share similar chemical transformation patterns, for which accuracy was calculated, comparing this set with manually curated data sets. DATA DESCRIPTION: The data were analyzed by a new method that naturally split each reaction into compound pairs and loner compounds, which we called architectures (Vazquez-Hernandez et al. in BMC Syst Biol 12:63, 2018). The data include a set of 7491 curated reactions from the KEGG-Ligand data set. The data are presented in two formats, a string format and a tree structure, both of which reflect the splitting process and the final architectures of each reaction. We are also reporting sets of reactions that show similar splitting patterns naturally grouped into clusters of tree structures. The compound pairs in each cluster were compared with the reactant pairs proposed by the KEGG-RCLASS data set, and a match precision value is also provided. These data were collected with the aim of providing research with a confident set of reactant pairs that is useful for selecting between alternative substrate-product pairs predicted by pathfinders.

Identification of reaction organization patterns that naturally cluster enzymatic transformations.

BACKGROUND: Metabolic reactions are chemical transformations commonly catalyzed by enzymes. In recent years, the explosion of genomic data and individual experimental characterizations have contributed to the construction of databases and methodologies for the analysis of metabolic networks. Some methodologies based on graph theory organize compound networks into metabolic functional categories without preserving biochemical pathways. Other methods based on chemical group exchange and atom flow trace the conversion of substrates into products in detail, which is useful for inferring metabolic pathways. METHODS: Here, we present a novel rule-based approach incorporating both methods that decomposes each reaction into architectures of compound pairs and loner compounds that can be organized into tree structures. We compared the tree structure-compound pairs to those reported in the KEGG-RPAIR dataset and obtained a match precision of 81%. The generated tree structures naturally clustered all reactions into general reaction patterns of compounds with similar chemical transformations. The match precision of each cluster was calculated and used to suggest reactant-pairs for which manual curation can be avoided because this is the main goal of the method. We evaluated catalytic processes in the clusters based on Enzyme Commission categories that revealed preferential use of enzyme classes. CONCLUSIONS: We demonstrate that the application of simple rules can enable the identification of reaction patterns reflecting metabolic reactions that transform substrates into products and the types of catalysis involved in these transformations. Our rule-based approach can be incorporated as the input in pathfinders or as a tool for the construction of reaction classifiers, indicating its usefulness for predicting enzyme catalysis.