Corynebacterium glutamicum as a model bacterium for the bioremediation of arsenic

Arsenic is an extremely toxic metalloid that, when present in high concentrations, severely threatens the biota and human health. Arsenic contamination of soil, water, and air is a global growing environmental problem due to leaching from geological formations, the burning of fossil fuels, wastes generated by the gold mining industry present in uncontrolled landfills, and improper agriculture or medical uses. Unlike organic contaminants, which are degraded into harmless chemical species, metals and metalloids cannot be destroyed, but they can be immobilized or transformed into less toxic forms. The ubiquity of arsenic in the environment has led to the evolution in microbes of arsenic defense mechanisms. The most common of these mechanisms is based on the presence of the arsenic resistance operon (ars), which codes for: (i) a regulatory protein, ArsR; (ii) an arsenite permease, ArsB; and (iii) an enzyme involved in arsenate reduction, ArsC. Corynebacterium glutamicum, which is used for the industrial production of amino acids and nucleotides, is one of the most arsenic-resistant microorganisms described to date (up to 12 mM arsenite and >400 mM arseniate). Analysis of the C. glutamicum genome revealed the presence of two complete ars operons (ars1 and ars2) comprising the typical three-gene structure arsRBC, with an extra arsC1´ located downstream from arsC1 (ars1 operon), and two orphan genes (arsB3 and arsC4). The involvement of both ars operons in arsenic resistance in C. glutamicum was confirmed by disruption and amplification of those genes. The strains obtained were resistant to up to 60 mM arsenite, one of the highest levels of bacterial resistance to arsenite so far described. Using tools for the genetic manipulation of C. glutamicum that were developed in our laboratory, we are attempting to obtain C. glutamicum mutant strains able to remove arsenic from contaminated water. [Int Microbiol 2006; 9(3):207-215

Cytoskeletal Proteins of Actinobacteria

Although bacteria are considered the simplest life forms, we are now slowly unraveling their cellular complexity. Surprisingly, not only do bacterial cells have a cytoskeleton but also the building blocks are not very different from the cytoskeleton that our own cells use to grow and divide. Nonetheless, despite important advances in our understanding of the basic physiology of certain bacterial models, little is known about Actinobacteria, an ancient group of Eubacteria. Here we review current knowledge on the cytoskeletal elements required for bacterial cell growth and cell division, focusing on actinobacterial genera such as Mycobacterium, Corynebacterium, and Streptomyces. These include some of the deadliest pathogens on earth but also some of the most prolific producers of antibiotics and antitumorals

Characterization of the promoter region of ftsZ from Corynebacterium glutamicum and controlled overexpression of FtsZ

Of the five promoters detected for the ftsZ gene in Corynebacterium glutamicum, three were located within the coding region of the upstream ftsQ gene and two within the intergenic ftsQ-ftsZ region. The most distant ftsZ promoter showed activity in Escherichia coli and controlled high-level transcriptional expression of ftsZ in C. glutamicum. Quantitative Western blotting showed that all five promoters were active during the exponential growth phase and down-regulated during stationary phase. This tightly controlled expression of ftsZ in C. glutamicum indicated that small changes in the amount of FtsZ protein strongly affect bacterial cell viability. The controlled overexpression of ftsZ in C. glutamicum, using the promoter of the gntK gene (PgntK), resulted in approximately 5-fold overproduction of FtsZ, an increase in cell diameter, and a highly variable localization of the protein as spirals or tangles throughout the cell. These results suggest that the intracellular concentration of FtsZ is critical for productive septum formation in C. glutamicum. Our observations provide insight into the mechanisms used by the coryneform group, which lacks actin homologs and many regulators of cell division, to control cell morphology. [Int Microbiol 2007; 10(4): 271-282

Influencia del rendimiento sobre el estilo decisional en jugadores de fútbol

El objetivo principal del presente trabajo fue analizar cómo el nivel de rendimiento afecta al perfil de estilo decisional. Se empleó una muestra de 247 jugadores de fútbol, de los cuales 106 pertenecían a la categoría infantil y 141 a la categoría cadete. La variable independiente fue el nivel de rendimiento, determinado por el puesto que ocupó cada equipo en la clasificación final de la competición. Las variables dependientes fueron la Competencia Decisional Percibida, la Ansiedad y Agobio al Decidir y el Compromiso en el Aprendizaje Decisional, variables que fueron medidas a partir del Cuestionario de Estilo de Toma de Decisiones (CETD) (Ruiz & Graupera, 2005). Los datos determinaron diferencias significativas, en función del nivel de rendimiento, en la variable Competencia Decisional Percibida, coincidiendo este resultado con estudios anteriores (Gaspar, 2001; García, Ruiz, & Graupera, 2009). Respecto a la Ansiedad y Agobio al Decidir, los deportistas mostraron más ansiedad a medida que se incrementaba el nivel de rendimiento, siendo este resultado opuesto al que se refleja en investigaciones precedentes (López, 2002; Jiménez, 2007). Por último, en el Compromiso en el Aprendizaje Decisional no se observaron diferencias en función del nivel de rendimiento, contradiciendo igualmente a estudios anteriores que reforzaban un aumento del compromiso en función del nivel de rendimiento (Ruiz et al., 2002; Jiménez, 2004)

Prognostic Value of Serum Paraprotein Response Kinetics in Patients With Newly Diagnosed Multiple Myeloma

Response kinetics is not well-established as a prognostic marker in multiple myeloma (MM). We developed a mathematical model to assess the prognostic value of serum monoclonal component (MC) response kinetics during 6 induction cycles in 373 newly diagnosed MM patients. The model calculated a resistance parameter that reflects the stagnation in the response after an initial descent, dividing the patients into two kinetics categories with significantly different progression-free survival (PFS). Introduction: Response kinetics is a well-established prognostic marker in acute lymphoblastic leukemia. The situation is not clear in multiple myeloma (MM) despite having a biomarker for response monitoring (monoclonal component [MC]). Materials and Methods: We developed a mathematical model to assess the prognostic value of serum MC response kinetics during 6 induction cycles, in 373 NDMM transplanted patients treated in the GEM2012Menos65 clinical trial. The model calculated a resistance parameter that reflects the stagnation in the response after an initial descent. Results: Two patient subgroups were defined based on low and high resistance, that respectively captured sensitive and refractory kinetics, with progression-free survival (PFS) at 5 years of 72% and 59% (HR 0.64, 95% CI 0.44-0.93; P =.02). Resistance significantly correlated with depth of response measured after consolidation (80.9% CR and 68.4% minimal residual disease negativity in patients with sensitive vs. 31% and 20% in those with refractory kinetics). Furthermore, it modulated the impact of reaching CR after consolidation; thus, within CR patients those with refractory kinetics had significantly shorter PFS than those with sensitive kinetics (median 54 months vs. NR; P =.02). Minimal residual disease negativity abrogated this effect. Our study also questions the benefit of rapid responders compared to late responders (5-year PFS 59.7% vs. 76.5%, respectively [P <.002]). Of note, 85% of patients considered as late responders were classified as having sensitive kinetics. Conclusion: This semi-mechanistic modeling of M-component kinetics could be of great value to identify patients at risk of early treatment failure, who may benefit from early rescue intervention strategies. (C) 2022 The Authors. Published by Elsevier Inc

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Cytoskeletal proteins of Actinobacteria. Int. J. Cell Biol. 2012:905832. doi: 10.1155/2012/905832

Although bacteria are considered the simplest life forms, we are now slowly unraveling their cellular complexity. Surprisingly, not only do bacterial cells have a cytoskeleton but also the building blocks are not very different from the cytoskeleton that our own cells use to grow and divide. Nonetheless, despite important advances in our understanding of the basic physiology of certain bacterial models, little is known about Actinobacteria, an ancient group of Eubacteria. Here we review current knowledge on the cytoskeletal elements required for bacterial cell growth and cell division, focusing on actinobacterial genera such as Mycobacterium, Corynebacterium, and Streptomyces. These include some of the deadliest pathogens on earth but also some of the most prolific producers of antibiotics and antitumorals

Characterization and Use of Catabolite-Repressed Promoters from Gluconate Genes in Corynebacterium glutamicum

The genes involved in gluconate catabolism (gntP and gntK) in Corynebacterium glutamicum are scattered in the chromosome, and no regulatory genes are apparently associated with them, in contrast with the organization of the gnt operon in Escherichia coli and Bacillus subtilis. In C. glutamicum, gntP and gntK are essential genes when gluconate is the only carbon and energy source. Both genes contain upstream regulatory regions consisting of a typical promoter and a hypothetical cyclic AMP (cAMP) receptor protein (CRP) binding region but lack the expected consensus operator region for binding of the GntR repressor protein. Expression analysis by Northern blotting showed monocistronic transcripts for both genes. The expression of gntP and gntK is not induced by gluconate, and the gnt genes are subject to catabolite repression by sugars, such as glucose, fructose, and sucrose, as was detected by quantitative reverse transcription-PCR (qRT-PCR). Specific analysis of the DNA promoter sequences (PgntK and PgntP) was performed using bifunctional promoter probe vectors containing mel (involved in melanin production) or egfp2 (encoding a green fluorescent protein derivative) as the reporter gene. Using this approach, we obtained results parallel to those from qRT-PCR. An applied example of in vivo gene expression modulation of the divIVA gene in C. glutamicum is shown, corroborating the possible use of the gnt promoters to control gene expression. glxR (which encodes GlxR, the hypothetical CRP protein) was subcloned from the C. glutamicum chromosomal DNA and overexpressed in corynebacteria; we found that the level of gnt expression was slightly decreased compared to that of the control strains. The purified GlxR protein was used in gel shift mobility assays, and a specific interaction of GlxR with sequences present on PgntP and PgntK fragments was detected only in the presence of cAMP

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Summary. Of the five promoters detected for the ftsZ gene in Corynebacterium glutamicum, three were located within the coding region of the upstream ftsQ gene and two within the intergenic ftsQ-ftsZ region. The most distant ftsZ promoter showed activity in Escherichia coli and controlled high-level transcriptional expression of ftsZ in C. glutamicum. Quantitative Western blotting showed that all five promoters were active during the exponential growth phase and down-regulated during stationary phase. This tightly controlled expression of ftsZ in C. glutamicum indicated that small changes in the amount of FtsZ protein strongly affect bacterial cell viability. The controlled overexpression of ftsZ in C. glutamicum, using the promoter of the gntK gene (PgntK), resulted in approximately 5-fold overproduction of FtsZ, an increase in cell diameter, and a highly variable localization of the protein as spirals or tangles throughout the cell. These results suggest that the intracellular concentration of FtsZ is critical for productive septum formation in C. glutamicum. Our observations provide insight into the mechanisms used by the coryneform group, which lacks actin homologs and many regulators of cell division, to control cell morphology. [Int Microbiol 2007; 10(4): 271-282