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Chapter 19 : Tracking the Rules of Transmission and Introgression with Networks

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Abstract:

It has been proposed that an organism and its microbes form an assemblage called a holobiont ( ). The human body and human genome along with gut microbes and their genomes can be seen as a dynamic holobiont system ( ), i.e., a superorganism amalgamating microbial and human attributes ( ). In this multipartite holobiont, the host genome provides the primary genome, while microbial genes constitute the “second human genome,” which is in fact a prokaryotic pangenome ( ). Whether the holobionts are units of selection is actively debated ( ), yet other aspects of their biology are less controversial, and holobionts are becoming a major object of study in biology. Among these uncontroversial features lies the observation that, by definition, a holobiont is home to several different modes of genetic transmission. In nuclear transmission, the genetic material is inherited from one individual (in parthenogenesis, for example) or, most of the time, from two individuals, whereas in organelle transmission (of mitochondria, for example), the material is mostly inherited from the mother, in animals ( ). Both types of transmission result directly from the reproduction of the host. This stands in contrast to transmission of the microbiota, that is, the acquisition (or loss) of microbes between host generations. In mammals, at birth, the microbiota is inherited from the mother, but this is not always the case for other animal groups, where it could also be inherited from the environment ( ). During the life of the individual, the microbiota may even evolve, depending on different factors, which are currently not well characterized (e.g., host constraints, diet, environment, and transmission between different hosts) ( ). The transmission of microbiomes differs in turn from the transmission of microbiotas, since it is no longer (or at least not only) microbes that are exchanged, acquired, or lost, but genes themselves. These genes may be carried by microbes, but also by viruses, plasmids, or other classes of mobile genetic elements (MGEs). For example, transmissions in the gut microbiome are in part due to horizontal gene transfer (HGT) ( ) because of the high cell density in microorganisms, and mediated by viruses—especially temperate prophages ( )—integrases, recombinases ( ), and conjugative transposons ( ). Finally, the transmission of microbes from the environment to the host has not been systematically taken into account ( ). As with any transmission, microbial transmission can be transient or permanent ( Fig. 1 ).

Citation: Vigliotti C, Bicep C, Bapteste E, Lopez P, Corel E. 2019. Tracking the Rules of Transmission and Introgression with Networks, p 345-365. In Baquero F, Bouza E, Gutiérrez-Fuentes J, Coque T (ed), Microbial Transmission. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MTBP-0008-2016
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Figure 1

Different types of transmission in holobionts. This figure presents different transmissions between holobionts, and between a holobiont and its environment. The holobiont is composed of two parts: the host and its microbial communities (microbiome from gut, skin, oral, etc.). When a host gives birth to another, the parent brings to its offspring mitochondria, cytoplasm, and genes (pink arrows). The transmission is from the parent to the progeny. In some cases, like in mammals, the mother gives microbiota and microbiome to her children (pink dashed arrow). A host from a holobiont may also bring to the microbial community of another holobiont microbes, MGEs (viruses and plasmids), genes, or metabolites (black arrow between holobionts). Otherwise, a holobiont may exchange with the environment MGEs (plasmids and viruses) or microbes (black arrows between holobiont and environment). Then, in a microbial community there are transmissions between the different elements: transmissions between microbes (for example, by reproduction [purple arrows] or lateral gene transfer [green arrows]) or transmission between microbes and MGEs (red arrows). In this case we talk about externalization.

Citation: Vigliotti C, Bicep C, Bapteste E, Lopez P, Corel E. 2019. Tracking the Rules of Transmission and Introgression with Networks, p 345-365. In Baquero F, Bouza E, Gutiérrez-Fuentes J, Coque T (ed), Microbial Transmission. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MTBP-0008-2016
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Figure 2

Networks as tools for describing relationships between holobionts and transmission in lizards’ gut microbiomes. (i) Sequence similarity network (SSN). The SSN is built by comparing ORFs from all lizards’ gut microbiomes, using an all-against-all BLASTP. The SSN contains five CCs, also called gene families. Nodes are ORFs and are colored depending on their taxonomic annotation (see legend). If two nodes are similar at a determined percentage of identity (e.g., 95%), then they are linked by an edge. (ii) Bipartite graph of lizards-gene families. Type I nodes are lizards, colored depending on their diet, and type II nodes are the five gene families described in part i. There is an edge between a type I node and a type II node if in the gene family you can find a sequence that is contained in the lizards’ gut microbiomes of the type I node. (iii) Bipartite graph of lizards-microbial classes. Type I nodes are lizards, and type II nodes are microbial classes. If in one lizard’s gut microbiome a microbial class is found, then there is a link between the type I node associated and the type II node associated. Type I nodes are colored depending on the diet of the lizard, and type II nodes are colored depending on the microbial class of ORFs. (iv) Bipartite graph of microbial classes-gene families. Type I nodes are microbial classes, and type II nodes are the five gene families described in part i. There is an edge between a type I node and a type II node if at least one ORF of the gene family of the type II node is from the microbial class of the type I node.

Citation: Vigliotti C, Bicep C, Bapteste E, Lopez P, Corel E. 2019. Tracking the Rules of Transmission and Introgression with Networks, p 345-365. In Baquero F, Bouza E, Gutiérrez-Fuentes J, Coque T (ed), Microbial Transmission. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MTBP-0008-2016
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Figure 3

Distribution of resident, potentially externalized, and highly externalized clusters according to their average pairwise identity percentage. Functional distributions were plotted for the three classes of clusters; resident clusters are in black, potentially externalized clusters in gray, and potentially highly externalized clusters in white.

Citation: Vigliotti C, Bicep C, Bapteste E, Lopez P, Corel E. 2019. Tracking the Rules of Transmission and Introgression with Networks, p 345-365. In Baquero F, Bouza E, Gutiérrez-Fuentes J, Coque T (ed), Microbial Transmission. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MTBP-0008-2016
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Figure 4

Functional distributions of resident, potentially externalized, and highly externalized clusters. Each cluster was assigned a COG annotation. (A) RNA processing and modification; (B) chromatin structure and dynamics; (C) energy production and conversion; (D) cell cycle control and mitosis; (E) amino acid metabolism and transport; (F) nucleotide metabolism and transport; (G) carbohydrate metabolism and transport; (H) coenzyme metabolism; (I) lipid metabolism; (J) translation; (K) transcription; (L) replication and repair; (M) cell wall/membrane/envelope biogenesis; (N) cell motility; (O) posttranslational modification, protein turnover, chaperone functions; (P) inorganic ion transport and metabolism; (Q) secondary structure; (R) general functional prediction only; (S) function unknown; (T) signal transduction; (U) intracellular trafficking and secretion; (V) Defense mechanisms; (W) Extracellular structures; (Z) cytoskeleton. Functional distributions were plotted for the three classes of clusters; resident clusters are in black, potentially externalized clusters in gray, and potentially highly externalized clusters in white. For each class of clusters, significantly enriched functional categories ( < 0.01; hypergeometric test, after adjusting for multiple testing) are identified by # (resident), + (potentially externalized), and * (potentially highly externalized).

Citation: Vigliotti C, Bicep C, Bapteste E, Lopez P, Corel E. 2019. Tracking the Rules of Transmission and Introgression with Networks, p 345-365. In Baquero F, Bouza E, Gutiérrez-Fuentes J, Coque T (ed), Microbial Transmission. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MTBP-0008-2016
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Figure 5

Distributions of ratio for resident, potentially externalized, and highly externalized clusters. Resident, potentially externalized, and highly externalized clusters are colored in black, gray, and white, respectively. The three distributions are not significantly different (Mann-Whitney-Wilcoxon test, < 0.01). ratios of >2 were pooled to simplify the display.

Citation: Vigliotti C, Bicep C, Bapteste E, Lopez P, Corel E. 2019. Tracking the Rules of Transmission and Introgression with Networks, p 345-365. In Baquero F, Bouza E, Gutiérrez-Fuentes J, Coque T (ed), Microbial Transmission. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MTBP-0008-2016
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Figure 6

Distributions of the taxonomic diversity for resident, potentially externalized, and highly externalized clusters. (Left) Distribution of clusters across microbial host genera; (right) distribution of clusters across microbial host phyla. Clusters are color-coded as above. Potentially externalized clusters have a significantly broader host range than resident clusters, and potentially highly externalized clusters have a significantly broader host range than resident clusters and potentially externalized clusters (Mann-Whitney-Wilcoxon test, < 0.01). Taxonomic diversities of >4 were pooled to simplify the display.

Citation: Vigliotti C, Bicep C, Bapteste E, Lopez P, Corel E. 2019. Tracking the Rules of Transmission and Introgression with Networks, p 345-365. In Baquero F, Bouza E, Gutiérrez-Fuentes J, Coque T (ed), Microbial Transmission. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MTBP-0008-2016
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Figure 7

Distribution of resident, potentially externalized, and highly externalized clusters across human hosts. Clusters are color-coded as above. Potentially externalized clusters have a significantly broader host range than resident clusters, and potentially highly externalized clusters have a significantly broader host range than resident clusters and potentially externalized clusters (Mann-Whitney-Wilcoxon test, < 0.01).

Citation: Vigliotti C, Bicep C, Bapteste E, Lopez P, Corel E. 2019. Tracking the Rules of Transmission and Introgression with Networks, p 345-365. In Baquero F, Bouza E, Gutiérrez-Fuentes J, Coque T (ed), Microbial Transmission. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MTBP-0008-2016
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Figure 8

A schematic representation of gene sharings within and between three “mobile elements + gut microbes + human individual” holobionts. Combinations of MGEs and of their direct hosts, e.g., the gut microbial cells, as well as of the human body, itself hosting gut microbes, form an integrated, multilevel, multipartite, dynamic biological system, also referred to as a holobiont. For each individual human, the black square represents a close-up of its gut microbiota (with gut microbial cells in brown and MGEs in purple) and of its gut microbiome (the genes contained within these microbial cells and MGEs). Genes are represented by colored rectangles; genes with the same color belong to the same gene family. The process of HGT, mediated by MGEs, is responsible for mobilizing genes between microbial cells. We demonstrated that gene families carried by a larger diversity of MGEs are more widely shared not only between gut microbes but also between individual human hosts, as shown for the red gene family. Thus, HGT is a key process for introducing genetic similarity at multiple consecutive host levels within and between holobionts.

Citation: Vigliotti C, Bicep C, Bapteste E, Lopez P, Corel E. 2019. Tracking the Rules of Transmission and Introgression with Networks, p 345-365. In Baquero F, Bouza E, Gutiérrez-Fuentes J, Coque T (ed), Microbial Transmission. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MTBP-0008-2016
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Figure 9

Tripartite graphs allow us to distinguish gene and microbial transmissions. In this tripartite graph, type I nodes are the hosts (lizards) and are colored depending on their diet. Middle nodes are microbial classes, and type II nodes are gene families. Type II nodes colored in red are gene families shared by insectivorous lizards only. Type II nodes colored in blue are gene families shared by omnivorous lizards only, and then those colored in purple are shared by insectivorous and omnivorous lizards. The tripartite graph allows division of gene families specific to a diet in two categories: gene families that are shared by microbial classes specific from a diet (group 1: gene families 1 and 2, encircled in red) and gene families that are shared by microbial classes nonspecific from a diet (group 2: gene families 3 and 4, encircled in red). In the first group, gene families are not necessarily involved in the diet of the lizards; they are in insectivorous lizards because all the microbial classes that contain them are specific from insectivorous lizards. In the second group, gene families are more likely involved in the diet because they are present in microbial classes that are not exclusive to insectivory. These two groups correspond to two different ways of transmission: the first group is a microbial transmission, whereas the second group is a gene transmission.

Citation: Vigliotti C, Bicep C, Bapteste E, Lopez P, Corel E. 2019. Tracking the Rules of Transmission and Introgression with Networks, p 345-365. In Baquero F, Bouza E, Gutiérrez-Fuentes J, Coque T (ed), Microbial Transmission. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MTBP-0008-2016
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