The dynamics of a family’s gut microbiota reveal variations on a theme

Abstract Background It is clear that the structure and function of the human microbiota has significant impact on maintenance of health and yet the factors that give rise to an adult microbiota are poorly understood. A combination of genetics, diet, environment, and life history are all thought to impact the development of the gut microbiome. Here we study a chronosequence of the gut microbiota found in eight individuals from a family consisting of two parents and six children ranging in age from two months to ten years old. Results Using 16S rRNA gene and metagenomic shotgun sequence data, it was possible to distinguish the family from a cohort of normal individuals living in the same geographic region and to differentiate each family member. Interestingly, there was a significant core membership to the family members’ microbiota where the abundance of this core accounted for the differences between individuals. It was clear that the introduction of solids represents a significant transition in the development of a mature microbiota. This transition was associated with increased diversity, decreased stability, and the colonization of significant abundances of Bacteroidetes and Clostridiales. Although the children and mother shared essentially the identical diet and environment, the children’s microbiotas were not significantly more similar to their mother than they were to their father. Conclusions This analysis underscores the complex interactions that give rise to a personalized microbiota and suggests the value of studying families as a surrogate for longitudinal studies.http://deepblue.lib.umich.edu/bitstream/2027.42/109502/1/40168_2014_Article_54.pd

Gene prediction with Glimmer for metagenomic sequences augmented by classification and clustering

Environmental shotgun sequencing (or metagenomics) is widely used to survey the communities of microbial organisms that live in many diverse ecosystems, such as the human body. Finding the protein-coding genes within the sequences is an important step for assessing the functional capacity of a metagenome. In this work, we developed a metagenomics gene prediction system Glimmer-MG that achieves significantly greater accuracy than previous systems via novel approaches to a number of important prediction subtasks. First, we introduce the use of phylogenetic classifications of the sequences to model parameterization. We also cluster the sequences, grouping together those that likely originated from the same organism. Analogous to iterative schemes that are useful for whole genomes, we retrain our models within each cluster on the initial gene predictions before making final predictions. Finally, we model both insertion/deletion and substitution sequencing errors using a different approach than previous software, allowing Glimmer-MG to change coding frame or pass through stop codons by predicting an error. In a comparison among multiple gene finding methods, Glimmer-MG makes the most sensitive and precise predictions on simulated and real metagenomes for all read lengths and error rates tested

Metagenomics - a guide from sampling to data analysis

Metagenomics applies a suite of genomic technologies and bioinformatics tools to directly access the genetic content of entire communities of organisms. The field of metagenomics has been responsible for substantial advances in microbial ecology, evolution, and diversity over the past 5 to 10 years, and many research laboratories are actively engaged in it now. With the growing numbers of activities also comes a plethora of methodological knowledge and expertise that should guide future developments in the field. This review summarizes the current opinions in metagenomics, and provides practical guidance and advice on sample processing, sequencing technology, assembly, binning, annotation, experimental design, statistical analysis, data storage, and data sharing. As more metagenomic datasets are generated, the availability of standardized procedures and shared data storage and analysis becomes increasingly important to ensure that output of individual projects can be assessed and compared

Discovering novel hydrolases from hot environments

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordNovel hydrolases from hot and other extreme environments showing appropriate performance and/or novel functionalities and new approaches for their systematic screening are of great interest for developing new processes, for improving safety, health and environment issues. Existing processes could benefit as well from their properties. The workflow, based on the HotZyme project, describes a multitude of technologies and their integration from discovery to application, providing new tools for discovering, identifying and characterizing more novel thermostable hydrolases with desired functions from hot terrestrial and marine environments. To this end, hot springs worldwide were mined, resulting in hundreds of environmental samples and thousands of enrichment cultures growing on polymeric substrates of industrial interest. Using high-throughput sequencing and bioinformatics, 15 hot spring metagenomes, as well as several sequenced isolate genomes and transcriptomes were obtained. To facilitate the discovery of novel hydrolases, the annotation platform Anastasia and a whole-cell bioreporter-based functional screening method were developed. Sequence-based screening and functional screening together resulted in about 100 potentially new hydrolases of which more than a dozen have been characterized comprehensively from a biochemical and structural perspective. The characterized hydrolases include thermostable carboxylesterases, enol lactonases, quorum sensing lactonases, gluconolactonases, epoxide hydrolases, and cellulases. Apart from these novel thermostable hydrolases, the project generated an enormous amount of samples and data, thereby allowing the future discovery of even more novel enzymes.European CommissionEuropean Union FP

Efectos maternos sobre el microbioma

[ES] El estudio del microbioma gastrointestinal es un campo de investigación emergente en el campo de la genética animal. En los últimos años, la reducción de los costes de la secuenciación masiva unido a la disponibilidad de bases de datos biológicas y herramientas bioinformáticas ha hecho posible este tipo de estudios. Los microorganismos gastrointestinales participan en la regulación de importantes funciones de barrera, metabólicas, de absorción, inmunológicas y de síntesis de vitaminas que influyen en el fenotipo de un individuo. Sin embargo, la composición microbiana puede variar entre individuos dando lugar a perfiles microbianos muy diferentes. Esta variación puede ser debida a factores externos como la alimentación o uso de antibióticos, pero también a factores internos como la genética del individuo o la composición microbiana vaginal que hereda el individuo de la madre. Habitualmente, estos dos últimos factores están confundidos y hay muy poca información del efecto materno en el microbioma de individuo sin que esté incluido el efecto genético del individuo. Por lo tanto, el objetivo de este trabajo fue estudiar la importancia del efecto materno en el microbioma separándolo del efecto genético del individuo. Para ello, se utilizaron individuos de dos líneas seleccionadas divergentemente para grasa intramuscular (GIM) durante diez generaciones. En la última generación de selección, se realizaron transferencias embrionarias aleatorias entre las dos líneas divergentes. Las hembras de ambas líneas recibieron tanto embriones de la línea alta (A) como de la línea baja (B). Estos individuos (75 gazapos) se genotiparon al nacer y se clasificaron en cuatro grupos: AA, BA, AB y BB, siendo la primera letra la línea a la que pertenecía la madre (A o B) y la segunda letra la línea a la que pertenece cada individuo (A o B). A las nueve semanas de edad se tomaron muestras del contenido del ciego de los conejos y se extrajo el ADN bacteriano. La secuenciación del genoma bacteriano se realizó por paired-end (150x2) en Illumina NextSeq 550. Un total de 2988 variables KEGG para la anotación funcional y 1138 unidades taxonómicas para el nivel jerárquico género fueron identificadas en los 75 individuos con la herramienta bioinformática SqueezeMeta. En ambas bases de datos, la funcional y la taxonómica, se realizó un filtrado inicial de muestras “outliers” identificadas a través de un análisis de componentes principales y de variables de baja prevalencia (porcentaje de datos que no son ceros) utilizando el paquete PIME. Posteriormente se imputaron los ceros y se aplicó la normalización weighted center log ratio (wCLR) para tratar los datos composicionales. Finalmente, se realizó el análisis multivariante de la proyección de estructuras latentes discriminantes (PLS-DA) con el objetivo de identificar las variables KEGG y las taxas que se diferenciaban entre grupos en cada una de las comparaciones. El análisis estadístico se realizó para tres comparaciones: AA vs BA (efecto materno cuando el individuo es A), AB vs BB (efecto materno cuando el individuo es B) y AA vs BB (efecto maternogenético). Los resultados del PLS-DA mostraron una clara separación entre grupos con una R2>0,8 y Q2>0,7 en la mayoría de los casos. Las variables KEGG responsables de la separación entre grupos fueron distintas entre las comparaciones. No obstante, las funciones KEGG más importantes relacionadas con estos KEGG no difirieron entre las comparaciones, destacando funciones relacionadas con el metabolismo de ácidos grasos y de aminoácidos. De manera similar, las taxas a nivel de género responsables de las separaciones de grupo fueron diferentes entre las comparaciones. A nivel de filo, los Firmicutes (70%) fueron los responsables de la discriminación entre grupos en las tres comparaciones. La mayoría de los géneros dentro de este filo pertenecían a la clase Clostridia (55%), siendo la familia Ruminococcae (25%) la más abundante en las tres comparaciones. Nuestro estudió proporcionó evidencia de la existencia de un efecto materno tanto a nivel funcional como taxonómico, permitiendo entender mejor la interacción entre la genética huésped y el microbioma. Sin embargo, la aplicación de estos conocimientos en producción animal requiere de una mayor investigación que permita definir cómo usar esta información para modificar el microbioma de los individuos.[EN] The study of the gastrointestinal microbiome is an emerging research field in the animal genetics domain. In recent years, the reduction in the costs of massive sequencing coupled with the availability of biological databases and bioinformatics tools has made this type of study possible. The gastrointestinal microorganisms are involved in the regulation of important barrier, metabolic, absorption, immunological and vitamin synthesis functions that influence the phenotype of an individual. However, the microbial composition can vary between individuals giving rise to very different microbial profiles. This variation may be due to external factors such as diet or use of antibiotics, but also to internal factors such as the individual's genetics or the vaginal microbial composition that the individual inherits from the mother. Usually, these last two factors are confused and there is very little information on the maternal effect on the individual's microbiome without including the genetic effect of the individual. Therefore, the objective of this work was to study the importance of the maternal effect in the microbiome, separating it from the genetic effect. For this, individuals from two lines divergently selected for intramuscular fat (GIM) were used along ten generations. In the last generation, random embryo transfers were performed between the two diverging lines.The females of both lines received embryos from both the high line (A) and from the low line (B). These individuals (75 rabbits) were genotyped at birth and classified into four groups: AA, BA, AB and BB, with the first letter being the line to which the mother belonged (A or B) and the second letter being the line to which the individual belonged. Nine-week of age samples were taken from the cecum content of rabbits and bacterial DNA was extracted. Bacterial genome sequencing was performed by paired-end (150x2) in Illumina NextSeq 550. A total of 2988 KEGG variables for functional annotation and 1138 taxonomic units for the gender hierarchical level were identified in the 75 individuals with the SqueezeMeta bioinformatics tool. In both the functional and taxonomic databases, an initial filtering of outlier samples detected with a principal component analysis was performed, as well as low prevalence variables (percentage of data that are not zeros) using the PIME package. Subsequently, the zeros were imputed and the weighted center log ratio (wCLR) normalization was applied to treat the compositional data. Finally, the multivariate analysis of the projection of discriminant latent structures (PLS-DA) was performed to identify the KEGG variables and the taxa that were differentiated between groups in each of the comparisons. Statistical analysis was performed for three comparisons: AA vs BA (maternal effect when the individual is A), AB vs BB (maternal effect when the individual is B), and AA vs BB (maternal-genetic effect). The PLS-DA results showed a clear separation between groups with an R2> 0.8 and Q2> 0.7 in most cases. At the functional level, functions related to fatty acid and amino acid metabolism stood out without differences between comparisons. However, the KEGG variables responsible for these functions were different between the comparisons. At phylum level, Firmicutes (70%) were responsible for intergroup discrimination in all three comparisons. Most of the genera within this phylum belonged to the Clostridia class (55%), with the Ruminococcae family (25%) being the most abundant in all three comparisons. Our study provided evidence that there was a maternal effect at both a functional and taxonomic level, allowing a better understanding of the interaction between host genetics and the microbiome. However, to extend these findings to livestock interaction will require further research and improved methodologies to define how use this information to modify the microbiome.[CA] L'estudi del microbioma gastrointestinal és un camp d'investigació emergent en el camp de la genètica animal. En els últims anys, la reducció dels costos de la seqüenciació massiva unit a la disponibilitat de bases de dades biològiques i eines bioinformáticas ha fet possible aquest tipus d'estudis. Els microorganismes gastrointestinals participen en la regulació d'importants funcions de barrera, metabòliques, d'absorció, immunològiques i de síntesis de vitamines que influeixen en el fenotip d'un individu. No obstant això, la composició microbiana pot variar entre individus donant lloc a perfils microbians molt diferents. Aquesta variació pot ser deguda a factors externs com l'alimentació o ús d'antibiòtics, però també a factors interns com la genètica de l'individu o la composició microbiana vaginal que hereta l'individu de la mare. Habitualment, aquests dos últims factors estan confosos i hi ha molt poca informació de l'efecte matern en el microbioma d'individu sense que estiga inclòs l'efecte genètic de l'individu. Per tant, l'objectiu d'aquest treball va ser estudiar la importància de l'efecte matern en el microbioma separant-lo de l'efecte genètic de l'individu. Per a això, es van utilitzar individus de dues línies seleccionades divergentment per a greix intramuscular (GIM) durant deu generacions. En l'última generació de selecció, es van realitzar transferències embrionàries aleatòries entre les dues línies divergents. Les femelles de totes dues línies van rebre tant embrions de la línia alta (A) com de la línia baixa (B). Aquests individus (75 llorigons) es van genotipar en nàixer i es van classificar en quatre grups: AA, BA, AB i BB, sent la primera lletra la línia a la qual pertanyia la mare (A o B) i la segona lletra la línia a la qual pertany cada individu (A o B). A les nou setmanes d'edat es van prendre mostres del contingut del cec dels conills i es va extraure l'ADN bacterià. La seqüenciació del genoma bacterià es va realitzar per paired-end (150x2) en Illumina NextSeq 550. Un total de 2988 variables KEGG per a l'anotació funcional i 1138 unitats taxonòmiques per al nivell jeràrquic gènere van ser identificades en els 75 individus amb l'eina bioinformática SqueezeMeta. En totes dues bases de dades, la funcional i la taxonòmica, es va realitzar un filtrat inicial de mostres “outliers” identificades a través d'una anàlisi de components principals i de variables de baixa prevalença (percentatge de dades que no són zeros) utilitzant el paquet PIME. Posteriorment es van imputar els zeros i es va aplicar la normalització weighted center log ràtio (wCLR) per a tractar les dades composicionals. Finalment, es va realitzar l'anàlisi multivariant de la projecció d'estructures latents discriminants (PLSDA) amb l'objectiu d'identificar les variables KEGG i les taxas que es diferenciaven entre grups en cadascuna de les comparacions. L'anàlisi estadística es va realitzar per a tres comparacions: AA vs BA (efecte matern quan l'individu és A), AB vs BB (efecte matern quan l'individu és B) i AA vs BB (efecte matern-genètic). Els resultats del PLS-DA van mostrar una clara separació entre grups amb una R2>0,8 i Q2>0,7 en la majoria dels casos. Les variables KEGG responsables de la separació entre grups van ser diferents entre les comparacions. No obstant això, les funcions KEGG més importants relacionades amb aquests KEGG no van diferir entre les comparacions, destacant funcions relacionades amb el metabolisme d'àcids grassos i d'aminoàcids. De manera similar, les taxas a nivell de gènere responsables de les separacions de grup van ser diferents entre les comparacions. A nivell de filo, els Firmicutes (70%) van ser els responsables de la discriminació entre grups en les tres comparacions. La majoria dels gèneres dins d'aquest tall pertanyien a la classe Clostridia (55%), sent la família Ruminococcae (25%) la més abundant en les tres comparacions. El nostre va proporcionar evidència de l'existència d'un efecte matern tant a nivell funcional com taxonòmic, permetent entendre millor la interacció entre la genètica del hoste i el microbioma. No obstant això, l'aplicació d'aquests coneixements en producció animal requereix d'una major investigació que permeta definir com usar aquesta informació per a modificar el microbioma dels individus.Mora Fenoll, M. (2020). Efectos maternos sobre el microbioma. http://hdl.handle.net/10251/148934TFG

Análisis de las poblaciones de microorganismos fijadores de nitrógeno del suelo aplicando procedimientos metagenómicos

En este trabajo de tesis doctoral se llevó a cabo el análisis de las poblaciones de microorganismos fijadores de nitrógeno del suelo aplicando análisis independientes del cultivo. Se analizaron suelos de la principal región agrícola de la Argentina, la región pampeana.Facultad de Ciencias Exacta

Taxonomic and functional characterisation of novel microbial diversity in sponges

Sponges can harbour diverse communities of microbial symbionts, collectively referred to as a holobiont. Sponge symbionts play important ecological and mutualistic roles, including cycling of carbon, nitrogen, and sulfur; provisioning the host with essential compounds; and producing bioactive metabolites that confer fitness advantages to the holobiont. Recent metagenomics and bioinformatics advances facilitate genomic reconstruction and metabolic characterisation of uncultured prokaryotic species. Leveraging these tools, I reconstructed 75 metagenome-assembled genomes (MAGs) that represent 21 novel sponge-associated species: ten Gammaproteobacteria, six Acidimicrobiia, and five Acidobacteriota. The gammaproteobacterial species were metabolically diverse, likely representing adaptations to diverse habitats associated with different sponge species. Two species from the Candidatus genus Azotimanducus comprised almost identical patterns of organoheterotrophy that likely enabled them to colonize the same sponge host, but differed in other features that likely allowed for niche partitioning and cohabitation. Unlike the sponge-associated Gammaproteobacteria, the Acidimicrobiia shared very similar genomic features. Of particular interest, sponge-associated Acidimicrobiia were predicted to produce bioactive compounds that may modulate host signalling pathways, suggesting a potential role in host health. The sponge-associated Acidobacteriota likely predominantly formed symbiosis with their hosts prior to the phylogenetic split between sponges and corals. All five acidobacteriotal species shared similar patterns of organoheterotrophy, likely allowing for scavenging organic substrates from the host environment. Another feature that was specifically enriched in the novel sponge-associated Acidobacteriota was their capacity to produce diverse B-vitamins, with Candidatus Versatilivorator vitaminiformans comprising the genetic capacity to produce all of them. All 21 novel species also comprised unique respiratory, degradation, biosynthetic, and defensive features that likely mediate their interactions with the corresponding hosts. Features shared by the majority of the species were also identified. Altogether, the comprehensive genomic characterisation of sponge symbionts in this thesis has uncovered unique and shared features, highlighting the importance of extensive surveys into uncultured sponge symbiont diversity and function