Identifying similarities at metabolic pathways with a strategy of Enzymatic Step Sequences.

An easy and fast strategy to compare functionally the metabolic maps is described. The KEGG metabolic maps are transformed into linear Enzymatic Step Sequences (ESS) using the Breadth First Search (BFS) algorithm. To do this, the KGML files are retrieved, and directed graph representations are created; where the nodes represent enzymes or enzymatic complexes, and the edges represent a compound, that is the 'product' from one reaction and a 'substrate' for the next. Then, a set of initialization nodes are selected, and used as the root for the construction of the BFS tree. This tree is used as a guide to the construction of the ESS. From each leaf (terminal node), the path is traced backwards until it reaches the root metabolic map and with two or fewer neighbors in the graph. In a second step, the ESS are compared with a Dynamic Programing algorithm, considering an "ad hoc" substitution matrix, and minimizing the global score. The dissimilarity values between two EC numbers ranged from 0 to 1, where 0 indicates similar EC numbers, and 1 indicates different EC numbers. Finally, the alignment is evaluated by using the normalized entropy-based function, considering a threshold of ≤ 0.27 as significant.•The KEGG metabolic maps are transformed into linear Enzymatic Step Sequences (ESS) using the Breadth First Search (BFS) algorithm.•Nodes represent enzymes or enzymatic complexes, and the edges represent a compound, that is 'product' from one reaction and a 'substrate' for the next.•The ESS are compared with a Dynamic Programing algorithm, considering an "ad hoc" substitution matrix, and minimizing the global score.

Complex networks analysis: Mexico's city metro system during the pandemic of COVID-19.

The COVID-19 (SARS-CoV-2) pandemic is changing the world, the way we socialize, as well as politics and public transport logistics and Mexico is not the exception. Authorities are designing new policies for public transport. The first restrictions include the close of different metro stations to ensure the social distance, avoid excess of passengers and reduce the demand, which also changes the metro system and the way it operates. In this paper a model is presented, based on the analysis and comparison of the Mexico's City Metro System as a total network as well as the network with stations that are closed due to COVID-19. Using complex networks will give to the population information about the connectivity, efficiency and robustness of the system, in order to be able to make improvements, have adequate planning, set up different policies to improve and meet the needs of the system after COVID-19.

Tracing the Repertoire of Promiscuous Enzymes along the Metabolic Pathways in Archaeal Organisms.

The metabolic pathways that carry out the biochemical transformations sustaining life depend on the efficiency of their associated enzymes. In recent years, it has become clear that promiscuous enzymes have played an important role in the function and evolution of metabolism. In this work we analyze the repertoire of promiscuous enzymes in 89 non-redundant genomes of the Archaea cellular domain. Promiscuous enzymes are defined as those proteins with two or more different Enzyme Commission (E.C.) numbers, according the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. From this analysis, it was found that the fraction of promiscuous enzymes is lower in Archaea than in Bacteria. A greater diversity of superfamily domains is associated with promiscuous enzymes compared to specialized enzymes, both in Archaea and Bacteria, and there is an enrichment of substrate promiscuity rather than catalytic promiscuity in the archaeal enzymes. Finally, the presence of promiscuous enzymes in the metabolic pathways was found to be heterogeneously distributed at the domain level and in the phyla that make up the Archaea. These analyses increase our understanding of promiscuous enzymes and provide additional clues to the evolution of metabolism in Archaea.

Attitudes, Knowledge, Use, and Recommendation of Complementary and Alternative Medicine by Health Professionals in Western Mexico.

BACKGROUND: The use of complementary and alternative medicine (CAM) has increased in many countries, and this has altered the knowledge, attitudes, and treatment recommendations of health professionals in regard to CAM. METHODS: Considering Mexican health professionals׳ lack of knowledge of CAM, in this report we surveyed 100 biomedical researchers and Ph.D. students and 107 specialized physicians and residents of a medical specialty in Guadalajara, México (Western Mexico) with a questionnaire to address their attitudes, knowledge, use, and recommendation of CAM. RESULTS: We observed that significantly more researchers had ever used CAM than physicians (83% vs. 69.2%, P = .023) and that only 36.4% of physicians had ever recommended CAM. Female researchers tended to have ever used CAM more than male researchers, but CAM use did not differ between genders in the physician group or by age in either group. Homeopathy, herbal medicine, and massage therapy were the most commonly used CAMs in both the groups. Physicians more frequently recommended homeopathy, massage therapy, and yoga to their patients than other forms of CAM, and physicians had the highest perception of safety and had taken the most courses in homeopathy. All CAMs were perceived to have high efficacy (>60%) in both the groups. The attitude questionnaire reported favorable attitudes toward CAM in both the groups. CONCLUSIONS: We observed a high rate of Mexican health professionals that had ever used CAM, and they had mainly used homeopathy, massage therapy, and herbal medicine. However, the recommendation rate of CAM by Mexican physicians was significantly lower than that in other countries, which is probably due to the lack of CAM training in most Mexican medical schools.

Correlation of Metabolic Variables with the Number of ORFs in Human Pathogenic and Phylogenetically Related Non- or Less-Pathogenic Bacteria.

To date, a few works have performed a correlation of metabolic variables in bacteria; however specific correlations with these variables have not been reported. In this work, we included 36 human pathogenic bacteria and 18 non- or less-pathogenic-related bacteria and obtained all metabolic variables, including enzymes, metabolic pathways, enzymatic steps and specific metabolic pathways, and enzymatic steps of particular metabolic processes, from a reliable metabolic database (KEGG). Then, we correlated the number of the open reading frames (ORF) with these variables and with the proportions of these variables, and we observed a negative correlation with the proportion of enzymes (r = -0.506, p < 0.0001), metabolic pathways (r = -0.871, p < 00.0001), enzymatic reactions (r = -0.749, p < 00.0001), and with the proportions of central metabolism variables as well as a positive correlation with the proportions of multistep reactions (r = 0.650, p < 00.0001) and secondary metabolism variables. The proportion of multifunctional reactions (r: -0.114, p = 0.41) and the proportion of enzymatic steps (r: -0.205, p = 0.14) did not present a significant correlation. These correlations indicate that as the size of a genome (measured in the number of ORFs) increases, the proportion of genes that encode enzymes significantly diminishes (especially those related to central metabolism), suggesting that when essential metabolic pathways are complete, an increase in the number of ORFs does not require a similar increase in the metabolic pathways and enzymes, but only a slight increase is sufficient to cope with a large genome.

Comparison of Metabolic Pathways in Escherichia coli by Using Genetic Algorithms.

In order to understand how cellular metabolism has taken its modern form, the conservation and variations between metabolic pathways were evaluated by using a genetic algorithm (GA). The GA approach considered information on the complete metabolism of the bacterium Escherichia coli K-12, as deposited in the KEGG database, and the enzymes belonging to a particular pathway were transformed into enzymatic step sequences by using the breadth-first search algorithm. These sequences represent contiguous enzymes linked to each other, based on their catalytic activities as they are encoded in the Enzyme Commission numbers. In a posterior step, these sequences were compared using a GA in an all-against-all (pairwise comparisons) approach. Individual reactions were chosen based on their measure of fitness to act as parents of offspring, which constitute the new generation. The sequences compared were used to construct a similarity matrix (of fitness values) that was then considered to be clustered by using a k-medoids algorithm. A total of 34 clusters of conserved reactions were obtained, and their sequences were finally aligned with a multiple-sequence alignment GA optimized to align all the reaction sequences included in each group or cluster. From these comparisons, maps associated with the metabolism of similar compounds also contained similar enzymatic step sequences, reinforcing the Patchwork Model for the evolution of metabolism in E. coli K-12, an observation that can be expanded to other organisms, for which there is metabolism information. Finally, our mapping of these reactions is discussed, with illustrations from a particular case.