Defining recovery potential in river restoration: a biological data-driven approach

Scientists and practitioners working on river restoration have made progress on understanding the recovery potential of rivers from geomorphological and engineering perspectives. We now need to build on this work to gain a better understanding of the biological processes involved in river restoration. Environmental policy agendas are focusing on nature recovery, reigniting debates about the use of “natural” reference conditions as benchmarks for ecosystem restoration. We argue that the search for natural or semi-natural analogues to guide restoration planning is inappropriate due to the absence of contemporary reference conditions. With a catchment-scale case study on the invertebrate communities of the Warwickshire Avon, a fifth-order river system in England, we demonstrate an alternative to the reference condition approach. Under our model, recovery potential is quantified based on the gap between observed biodiversity at a site and the biodiversity predicted to occur in that location under alternative management scenarios. We predict that commonly applied restoration measures such as reduced nutrient inputs and the removal of channel resectioning could be detrimental to invertebrate diversity, if applied indiscriminately and without other complementary measures. Instead, our results suggest considerable potential for increases in biodiversity when restoration measures are combined in a way that maximises biodiversity within each water body

Evolution of Intra-specific Regulatory Networks in a Multipartite Bacterial Genome

<div><p>Reconstruction of the regulatory network is an important step in understanding how organisms control the expression of gene products and therefore phenotypes. Recent studies have pointed out the importance of regulatory network plasticity in bacterial adaptation and evolution. The evolution of such networks within and outside the species boundary is however still obscure. <i>Sinorhizobium meliloti</i> is an ideal species for such study, having three large replicons, many genomes available and a significant knowledge of its transcription factors (TF). Each replicon has a specific functional and evolutionary mark; which might also emerge from the analysis of their regulatory signatures. Here we have studied the plasticity of the regulatory network within and outside the <i>S. meliloti</i> species, looking for the presence of 41 TFs binding motifs in 51 strains and 5 related rhizobial species. We have detected a preference of several TFs for one of the three replicons, and the function of regulated genes was found to be in accordance with the overall replicon functional signature: house-keeping functions for the chromosome, metabolism for the chromid, symbiosis for the megaplasmid. This therefore suggests a replicon-specific wiring of the regulatory network in the <i>S. meliloti</i> species. At the same time a significant part of the predicted regulatory network is shared between the chromosome and the chromid, thus adding an additional layer by which the chromid integrates itself in the core genome. Furthermore, the regulatory network distance was found to be correlated with both promoter regions and accessory genome evolution inside the species, indicating that both pangenome compartments are involved in the regulatory network evolution. We also observed that genes which are not included in the species regulatory network are more likely to belong to the accessory genome, indicating that regulatory interactions should also be considered to predict gene conservation in bacterial pangenomes.</p></div

Regulon downstream genes.

<p>Regulatory network general statistics over the strains used in this study.</p><p>^<i>a</i> Position according to the Rm1021 reference strain;</p><p>^<i>b</i> Mean Absolute Deviation;</p><p>NA: not defined.</p><p>Regulon downstream genes.</p

TFs preferentially associated with a replicon.

<p>a) K-means clustering of the normalized proportion of genes regulated in each of the three main replicons of <i>S. meliloti</i>, visualized in a two-dimensional PCA. The dark blue and cyan clusters contain TFs with no clear replicon preference; b) Variability in the number of regulatory links in the same replicon and between replicons. All differences are significant (t-test p-value < 0.05).</p

Regulatory network dynamics.

<p>a) Graphical representation of the six states in which each regulatory link (a gene found with a TFBS in at least one genome) can be found in the <i>S. meliloti</i> species and between the outgroup species; b) states probabilities and states transitions probabilities inside the <i>S. meliloti</i> species: nodes and edges sizes are proportional to the probability in the model. For each state, the sum of transition probabilities is one; transition probabilities below 0.1 are not shown; c) states probabilities and states transitions probabilities between the outgroup species.</p

Correlations between pangenome diversity and regulatory network distances.

<p>R and S indicate the Pearson’s and Spearman’s correlation coefficients between the regulatory network and each pangenome partition distances (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004478#sec008" target="_blank">Materials and Methods</a> for the definition of the distances metrics used here). Outliers have been defined using a Z-score threshold of 3.5 on the mean absolute deviation of the distances. a) correlations within the <i>S. meliloti</i> species for the accessory genome; b) correlations within the <i>S. meliloti</i> species for coding and upstream regions; and c) correlation between the outgroups.</p

Regulon conservation.

<p>Regulatory network conservation in <i>S. meliloti</i> and near rhizobial species. For each regulator the number of conserved downstream genes over the average regulon size is reported.</p><p>^<i>a</i><i>S. meliloti</i> strain Rm1021 is also considered.</p><p>NA: not defined.</p><p>Regulon conservation.</p

Variability in regulon size.

<p>Color intensity indicates the number of downstream regulated genes in each strain; gray squares indicate the TF absence in the genome of that particular strain. Blue squares indicate that there are more than 64 genes predicted to be under the control of the TF. TFs are colored according to the replicon they belong to: red for chromosome, green for the pSymA megaplasmid and blue for the pSymB chromid.</p