It is easy for today’s students and researchers to believe that modern bioinformatics emerged recently to assist next-generation sequencing data analysis. However, the very beginnings of bioinformatics occurred more than 50 years ago, when desktop computers were still a hypothesis and DNA could not yet be sequenced. The foundations of bioinformatics were laid in the early 1960s with the application of computational methods to protein sequence analysis (notably, de novo sequence assembly, biological sequence databases and substitution models). Later on, DNA analysis also emerged due to parallel advances in (i) molecular biology methods, which allowed easier manipulation of DNA, as well as its sequencing, and (ii) computer science, which saw the rise of increasingly miniaturized and more powerful computers, as well as novel software better suited to handle bioinformatics tasks. In the 1990s through the 2000s, major improvements in sequencing technology, along with reduced costs, gave rise to an exponential increase of data. The arrival of ‘Big Data’ has laid out new challenges in terms of data mining and management, calling for more expertise from computer science into the field. Coupled with an ever-increasing amount of bioinformatics tools, biological Big Data had (and continues to have) profound implications on the predictive power and reproducibility of bioinformatics results. To overcome this issue, universities are now fully integrating this discipline into the curriculum of biology students. Recent subdisciplines such as synthetic biology, systems biology and whole-cell modeling have emerged from the ever-increasing complementarity between computer science and biology.

The major human bacterial pathogenPseudomonas aeruginosacauses multidrug-resistant infections in people with underlying immunodeficiencies or structural lung diseases such as cystic fibrosis (CF). We show that a few environmental isolates, driven by horizontal gene acquisition, have become dominant epidemic clones that have sequentially emerged and spread through global transmission networks over the past 200 years. These clones demonstrate varying intrinsic propensities for infecting CF or non-CF individuals (linked to specific transcriptional changes enabling survival within macrophages); have undergone multiple rounds of convergent, host-specific adaptation; and have eventually lost their ability to transmit between different patient groups. Our findings thus explain the pathogenic evolution ofP. aeruginosaand highlight the importance of global surveillance and cross-infection prevention in averting the emergence of future epidemic clones.

Shannon’s entropy is a popular alpha diversity metric because it estimates both richness and evenness in a single equation. However, since its value is dependent on both those parameters, there is theoretically an infinite number of richness/evenness value combinations translating into the same index score.

Walleye (Sander vitreus) is the second most fished freshwater species in Canada. While much sought by anglers, walleye also supports substantial commercial fisheries. To cope with the recent decline of wild walleye populations, fish farmers produce juveniles for lake stocking. However, walleye breeding is particularly tedious, mostly due to high disease susceptibility at larval and juvenile developmental stages. The main threat is the columnaris disease, which is caused by Flavobacterium columnare, an opportunistic bacteria. As F. columnare strains exhibit increasing antibiotic resistance, there is a strong need to develop efficient and sustainable alternative strategies to control columnaris disease. Bacterial probiotics have been shown to mitigate infections either by enhancing host immune response or by inhibiting pathogen growth. Being successfully assessed in many fish/pathogen combinations, we developed a tailored probiotic strategy for walleye to prevent and treat columnaris disease. Thirty-seven endogenous bacterial strains were isolated from healthy walleye’s skin and gut, were tested in vitro against F. columnare. Significant antagonistic effect against F. columare was measured for two out of thirty-seven endogenous strains. These two probiotic strains were identified as Pseudomonas fluorescens. The antagonistic effect of these two successful probiotics was further validated in vivo during a two months stress trial: groups receiving probiotic treatments showed on average 53.74% survival improvement

The opportunistic pathogen Pseudomonas aeruginosa chronically infects the lungs of patients with cystic fibrosis (CF). During infection the bacteria evolve and adapt to the lung environment. Here we use genomic, transcriptomic and phenotypic approaches to compare multiple isolates of P. aeruginosa collected more than 20 years apart during a chronic infection in a CF patient. Complete genome sequencing of the isolates, using short- and long-read technologies, showed that a genetic bottleneck occurred during infection and was followed by diversification of the bacteria. A 125 kb deletion, an 0.9 Mb inversion and hundreds of smaller mutations occurred during evolution of the bacteria in the lung, with an average rate of 17 mutations per year. Many of the mutated genes are associated with infection or antibiotic resistance. RNA sequencing was used to compare the transcriptomes of an earlier and a later isolate. Substantial reprogramming of the transcriptional network had occurred, affecting multiple genes that contribute to continuing infection. Changes included greatly reduced expression of flagellar machinery and increased expression of genes for nutrient acquisition and biofilm formation, as well as altered expression of a large number of genes of unknown function. Phenotypic studies showed that most later isolates had increased cell adherence and antibiotic resistance, reduced motility, and reduced production of pyoverdine (an iron-scavenging siderophore), consistent with genomic and transcriptomic data. The approach of integrating genomic, transcriptomic and phenotypic analyses reveals, and helps to explain, the plethora of changes that P. aeruginosa undergoes to enable it to adapt to the environment of the CF lung during a chronic infection.

Aeromonas sobria is a mesophilic motile aeromonad currently depicted as an opportunistic pathogen, despite increasing evidence of mutualistic interactions in salmonid fish. However, the determinants of its host-microbe associations, either mutualistic or pathogenic, remain less understood than for other aeromonad species. On one side, there is an over-representation of pathogenic interactions in the A. sobria literature, of which only three articles to date report mutualistic interactions; on the other side, genomic characterization of this species is still fairly incomplete as only two draft genomes were published prior to the present work. Consequently, no study specifically investigated the biodiversity of A. sobria. In fact, the investigation of A. sobria as a species complex may have been clouded by: (i) confusion with A. veronii biovar sobria because of their similar biochemical profiles, and (ii) the intrinsic low resolution of previous studies based on 16S rRNA gene sequences and multilocus sequence typing. So far, the only high-resolution, phylogenomic studies of the genus Aeromonas included one A. sobria strain (CECT 4245 / Popoff 208), making it impossible to robustly conclude on the phylogenetic intra-species diversity and the positioning among other Aeromonas species. To further understand the biodiversity and the spectrum of host-microbe interactions in A. sobria as well as its potential genomic diversity, we assessed the genomic and phenotypic heterogeneity among five A. sobria strains: two clinical isolates recovered from infected fish (JF2635 and CECT 4245), one from an infected amphibian (08005) and two recently isolated brook charr probionts (TM12 and TM18) which inhibit in vitro growth of A. salmonicida subsp. salmonicida (a salmonid fish pathogen). A phylogenomic assessment including 2,154 softcore genes corresponding to 946,687 variable sites from 33 Aeromonas genomes confirms the status of A. sobria as a distinct species divided in two subclades, with 100% bootstrap support. The phylogenomic split of A. sobria in two subclades is corroborated by a deep dichotomy between all five A. sobria strains in terms of inhibitory effect against A. salmonicida subsp. salmonicida, gene contents and codon usage. Finally, the antagonistic effect of A. sobria strains TM12 and TM18 suggests novel control methods against A. salmonicida subsp. salmonicida.