In Silico Exploration of Mycobacterium tuberculosis Metabolic Networks Shows Host-Associated Convergent Fluxomic Phenotypes

Mycobacterium tuberculosis, the causative agent of tuberculosis, is composed of several lineages characterized by a genome identity higher than 99%. Although the majority of the lineages are associated with humans, at least four lineages are adapted to other mammals, including different M. tuberculosis ecotypes. Host specificity is associated with higher virulence in its preferred host in ecotypes such as M. bovis. Deciphering what determines the preference of the host can reveal host-specific virulence patterns. However, it is not clear which genomic determinants might be influencing host specificity. In this study, we apply a combination of unsupervised and supervised classification methods on genomic data of ~27,000 M. tuberculosis clinical isolates to decipher host-specific genomic determinants. Host-specific genomic signatures are scarce beyond known lineage-specific mutations. Therefore, we integrated lineage-specific mutations into the iEK1011 2.0 genome-scale metabolic model to obtain lineage-specific versions of it. Flux distributions sampled from the solution spaces of these models can be accurately separated according to host association. This separation correlated with differences in cell wall processes, lipid, amino acid and carbon metabolic subsystems. These differences were observable when more than 95% of the samples had a specific growth rate significantly lower than the maximum achievable by the models. This suggests that these differences might manifest at low growth rate settings, such as the restrictive conditions M. tuberculosis suffers during macrophage infection

Evaluating the Applicability of Data-Driven Dietary Patterns to Independent Samples with a Focus on Measurement Tools for Pattern Similarity

BACKGROUND: Diet is a key modifiable risk for many chronic diseases, but it remains unclear whether dietary patterns from one study sample are generalizable to other independent populations. OBJECTIVE: The primary objective of this study was to assess whether data-driven dietary patterns from one study sample are applicable to other populations. The secondary objective was to assess the validity of two criteria of pattern similarity. METHODS: Six dietary patterns-Western (n=3), Mediterranean, Prudent, and Healthy- from three published studies on breast cancer were reconstructed in a case-control study of 973 breast cancer patients and 973 controls. Three more internal patterns (Western, Prudent, and Mediterranean) were derived from this case-control study's own data. STATISTICAL ANALYSIS: Applicability was assessed by comparing the six reconstructed patterns with the three internal dietary patterns, using the congruence coefficient (CC) between pattern loadings. In cases where any pair met either of two commonly used criteria for declaring patterns similar (CC ≥0.85 or a statistically significant [P0.9) to their corresponding dietary pattern derived from the case-control study's data. Similar associations with risk for breast cancer were found in all pairs of dietary patterns that had high CC but not in all pairs of dietary patterns with statistically significant correlations. CONCLUSIONS: Similar dietary patterns can be found in independent samples. The P value of a correlation coefficient is less reliable than the CC as a criterion for declaring two dietary patterns similar. This study shows that diet scores based on a particular study are generalizable to other populations.This study was funded by Fundación Científica Asociación Española Contra el Cáncer (Scientific Foundation of the Spanish Association Against Cancer), the Spanish Ministry of Economy and Competitiveness (IJCI-2014-20900); Fundación Cerveza y Salud 2005 (Beer and Health Foundation 2005), Sociedad Española de Oncología Médica (Spanish Society of Medical Oncology), Federación de Mujeres con Cáncer de Mama (Association of Women with Breast Cancer) (EPY 1169-10 grant) and Association of Women with Breast Cancer from Elche (EPY 1394/15 grant)

Famílies botàniques de plantes medicinals

Facultat de Farmàcia, Universitat de Barcelona. Ensenyament: Grau de Farmàcia, Assignatura: Botànica Farmacèutica, Curs: 2013-2014, Coordinadors: Joan Simon, Cèsar Blanché i Maria Bosch.Els materials que aquí es presenten són els recull de 175 treballs d’una família botànica d’interès medicinal realitzats de manera individual. Els treballs han estat realitzat per la totalitat dels estudiants dels grups M-2 i M-3 de l’assignatura Botànica Farmacèutica durant els mesos d’abril i maig del curs 2013-14. Tots els treballs s’han dut a terme a través de la plataforma de GoogleDocs i han estat tutoritzats pel professor de l’assignatura i revisats i finalment co-avaluats entre els propis estudiants. L’objectiu principal de l’activitat ha estat fomentar l’aprenentatge autònom i col·laboratiu en Botànica farmacèutica

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Deciphering the molecular bases of virulence-related phenotypes through multi-omic approaches

Virulence is defined as the degree of disease severity and lethality produced by a pathogen and is conditioned by virulence factors, which vary depending on the pathogen and determine the range of hosts it can infect. As a result, virulence is a complex phenotype, dependent on multiple molecular determinants. Omic techniques are thus a good way to investigate it. This thesis discusses two virulence-related phenotypes in two pathogens: surfactant biosynthesis in Pseudomonas aeruginosa and host specificity in Mycobacterium tuberculosis. P. aeruginosa is an opportunistic gram-negative pathogen that infects immunocompromised patients. Its collective behaviors are crucial during infection. They require the secretion of biosurfactants, secondary metabolites that enable the bacteria to spread through moist surfaces, which is highly regulated by environmental cues. Conversely, M. tuberculosis is a mammal obligate pathogen whose first infection targets are the macrophages. There are several M. tuberculosis lineages, which present host association. Identifying the factors that affect the inclination towards a host can show host-specific virulence patterns. Here, through a multi-omic approach we gained insight about these two phenotypes. We observed that surfactant production is inconsistent across P. aeruginosa’s phylogeny and added an additional layer of regulation of this phenotype, dependent on oxidative stress. Regarding M. tuberculosis, through metabolic modeling we predicted the lineage-specific genomic differences to produce host-correlated convergent alterations in metabolic pathways important for its virulence. Furthermore, we pinpointed candidate genes for their involvement in host specificity, such as Phospholipase C ones. Finally, by using an in vitro infection model we expanded the current knowledge about the adaptation of animal-associated lineages to their hosts and found experimental evidence supporting the involvement of the phospholipase C plcC gene in the adaptation to humans. Metabolism was central in the exploration of these phenotypes. Because it is at the end of the biological information chain, it is closer to phenotype than any other omic dataset. Metabolomics gave a comprehensive picture of the researched biological systems, allowing for the formulation of hypotheses that could later be empirically tested. The bioinformatic pipelines developed in this thesis can be applied to the study of other complex phenotypes in other organisms. The knowledge gained about these virulence related phenotypes might serve as a basis for developing new therapies against these pathogens

Goigs a Santa María de l'Olivar, venerada en el seu Santuari de Sóller (Mallorca)

Impremta Pizà

Goigs a Santa María de l'Olivar, venerada en el seu Santuari de Sóller (Mallorca)

Impremta Pizà

Decyphering Mycobacterium tuberculosis host specificity through the integration of genomics and infection biology

Resumen del póster presentado al 41st Annual Congress of the European Society of Mycobacteriology (ESM), celebrado de forma virtual del 28 al 29 de junio de 2019.Mycobacterium tuberculosis is the microorganism that produces tuberculosis, which is among the top 10 causes of death worldwide. Most of its lineages infect predominantly humans, except for four, which infect a wide range of other mammals. We will refer to them as animal-associated lineages. As understanding the genetic basis of host specificity can inform about the virulence factors of M. tuberculosis in each host, our objective is to decipher if host specificity correlates with virulence in vitro, and with lineage specific genomic signatures. We combined experiments in macrophage infection model with whole genome sequencing analysis of ~35.000 clinical M. tuberculosis strains to determine genomic specific signatures of the bacteria during the infectious process. We observed different genomic signatures between human and animal M. tuberculosis associated lineages. A differential signature was observed in three of the four genes that encode for phospholipase C in M. tuberculosis (plcABC) and PPE38. These genes are part of a previously described Region of Difference (RD), RD5, which is unevenly distributed between animal- and human-associated lineages. This region is completely lost in two and partially lost in one out of four of the animal lineages, while present in most of the isolates belonging to the human-associated lineages. Phylogenomic analysis showed that these deletions happened several times during evolution indicating the loss of these regions could be under differential selection pressure in animal- and human-associated strains. Because phospholipase C has been previously linked to M. tuberculosis virulence, we explored the differential expression of these genes between lineages infecting macrophages coming from different hosts.Peer reviewe

Integrating genomics and infection biology to decipher differences between human and animal associated M. tuberculosis lineages

Resumen del póster presentado al XLII Congreso de la Sociedad Española de Genética, celebrado de forma virtual del 14 al 18 de junio de 2021.Mycobacterium tuberculosis, which causes tuberculosis, is of the top 10 causes of death worldwide caused by an infectious disease. The majority of the lineages infect predominantly humans, except four lineages that infect a wide range of other mammals, and we refer to as animal-associated lineages. Because understanding the genetic basis of host specificity can inform about the virulence factors of M. tuberculosis in each host, our objective is to decipher is host specificity correlates with virulence in vitro, and with lineage specific genomic signatures. We combined experiments in macrophage infection model with whole genome sequencing analysis of 35.000 clinical M. tuberculosis strains representing all ecotypes to determine genomic specific signatures of the bacteria during the infectious process. We observed different genomics signatures between human and animal M. tuberculosis associated lineages. A differential signature was observed in three of the four genes that encode for phospholipase C in M. tuberculosis, lost in three out of four animal lineages, and present in the human lineages. Phylogenomic analysis showed that these deletions happened several times during evolution indicating a convergence in the loss of these regions that could be under differential selection pressure in animal and human associated strains. Because phospholipase C has been previously linked to M. tuberculosis virulence, we explored the differential expression of these genes between lineages infecting two different host cells.M.C. is supported by Ramón y Cajal program from Ministerio de Ciencia. This work was funded by Generalitat Valenciana (SEJI/2019/011) and Ministerio de ciencia e innovación (RTI2018-094399-A-I00).Peer reviewe