Marie Filteau

Gene Coexpression Networks Reveal Key Drivers of Phenotypic Divergence in Lake Whitefish

A functional understanding of processes involved in adaptive divergence is one of the awaiting opportunities afforded by high-throughput transcriptomic technologies. Functional analysis of coexpressed genes has succeeded in the biomedical field in identifying key drivers of disease pathways. However, in ecology and evolutionary biology, functional interpretation of transcriptomic data is still limited. Here, we used Weighted Gene Co-Expression Network Analysis (WGCNA) to identify modules of coexpressed genes in muscle and brain tissue of a lake whitefish backcross progeny. Modules were connected to gradients of known adaptive traits involved in the ecological speciation process between benthic and limnetic ecotypes. Key drivers, that is, hub genes of functional modules related to reproduction, growth, and behavior were identified, and module preservation was assessed in natural populations. Using this approach, we identified modules of coexpressed genes involved in phenotypic divergence and their key drivers, and further identified a module part specifically rewired in the backcross progeny. Functional analysis of transcriptomic data can significantly contribute to the understanding of the mechanisms underlying ecological speciation. Our findings point to bone morphogenetic protein and calcium signaling as common pathways involved in coordinated evolution of trophic behavior, trophic morphology (gill rakers), and reproduction. Results also point to pathways implicating hemoglobins and constitutive stress response (HSP70) governing growth in lake whitefish.

Nonparallelism in MHCIIβ diversity accompanies nonparallelism in pathogen infection of lake whitefish (Coregonus clupeaformis) species pairs as revealed by next-generation sequencing.

Major histocompatibility (MHC) immune system genes may evolve in response to pathogens in the environment. Because they also may affect mate choice, they are candidates for having great importance in ecological speciation. Here, we use next‐generation sequencing to test the general hypothesis of parallelism in patterns of MHCIIβ diversity and bacterial infections among five dwarf and normal whitefish sympatric pairs. A second objective was to assess the functional relationships between specific MHCIIβ alleles and pathogens in natural conditions. Each individual had between one and four alleles, indicating two paralogous loci. In Cliff Lake, the dwarf ecotype was monomorphic for the most common allele. In Webster Lake, the skew in the allelic distribution was towards the same allele but in the normal ecotype, underscoring the nonparallel divergence among lakes. Our signal of balancing selection matched putative peptide binding region residues in some cases, but not in others, supporting other recent findings of substantial functional differences in fish MHCIIβ compared with mammals. Individuals with fewer alleles were less likely to be infected; thus, we found no evidence for the heterozygote advantage hypothesis. MHCIIβ alleles and pathogenic bacteria formed distinct clusters in multivariate analyses, and clusters of certain alleles were associated with clusters of pathogens, or sometimes the absence of pathogens, indicating functional relationships at the individual level. Given that patterns of MHCIIβ and bacteria were nonparallel among dwarf and normal whitefish pairs, we conclude that pathogens driving MHCIIβ evolution did not play a direct role in their parallel phenotypic evolution.

Seasonal and regional diversity of maple sap microbiota revealed using community PCR fingerprinting and 16S rRNA gene clone libraries.

An arbitrary primed community PCR fingerprinting technique based on capillary electrophoresis was developed to study maple sap microbial community characteristics among 19 production sites in Québec over the tapping season. Presumptive fragment identification was made with corresponding fingerprint profiles of bacterial isolate cultures. Maple sap microbial communities were subsequently compared using a representative subset of 13 16S rRNA gene clone libraries followed by gene sequence analysis. Results from both methods indicated that all maple sap production sites and flow periods shared common microbiota members, but distinctive features also existed. Changes over the season in relative abundance of predominant populations showed evidence of a common pattern. Pseudomonas (64%) and Rahnella (8%) were the most abundantly and frequently represented genera of the 2239 sequences analyzed. Janthinobacterium, Leuconostoc, Lactococcus, Weissella, Epilithonimonas and Sphingomonas were revealed as occasional contaminants in maple sap. Maple sap microbiota showed a low level of deep diversity along with a high variation of similar 16S rRNA gene sequences within the Pseudomonas genus. Predominance of Pseudomonas is suggested as a typical feature of maple sap microbiota across geographical regions, production sites, and sap flow periods.

Systematic identification of signal integration by protein kinase A.

Significance Protein kinase A (PKA) complexes are versatile signaling enzymes controlling homeostasis in eukaryotes. This enzyme is involved in multiple functions under physiological and pathological conditions in humans and governs the virulence of many pathogenic fungi. Here we systematically identify PKA regulators in yeast. Notably, we describe signaling to PKA that involves feedback from the cellular recycling process, autophagy. We also uncover a posttranslational modification, acetylation, that regulates PKA activity in both yeast and mammals, and we show that this mechanism impacts aging. Thus, we identify what regulates PKA as a first step toward the ability to cure diseases and infections, for instance, by providing new candidate genes for drug targeting in health research and antifungals for agricultural and medical purposes. Cellular processes and homeostasis control in eukaryotic cells is achieved by the action of regulatory proteins such as protein kinase A (PKA). Although the outbound signals from PKA directed to processes such as metabolism, growth, and aging have been well charted, what regulates this conserved regulator remains to be systematically identified to understand how it coordinates biological processes. Using a yeast PKA reporter assay, we identified genes that influence PKA activity by measuring protein–protein interactions between the regulatory and the two catalytic subunits of the PKA complex in 3,726 yeast genetic-deletion backgrounds grown on two carbon sources. Overall, nearly 500 genes were found to be connected directly or indirectly to PKA regulation, including 80 core regulators, denoting a wide diversity of signals regulating PKA, within and beyond the described upstream linear pathways. PKA regulators span multiple processes, including the antagonistic autophagy and methionine biosynthesis pathways. Our results converge toward mechanisms of PKA posttranslational regulation by lysine acetylation, which is conserved between yeast and humans and that, we show, regulates protein complex formation in mammals and carbohydrate storage and aging in yeast. Taken together, these results show that the extent of PKA input matches with its output, because this kinase receives information from upstream and downstream processes, and highlight how biological processes are interconnected and coordinated by PKA.

Evolutionary rescue by compensatory mutations is constrained by genomic and environmental backgrounds

Since deleterious mutations may be rescued by secondary mutations during evolution, compensatory evolution could identify genetic solutions leading to therapeutic targets. Here, we tested this hypothesis and examined whether these solutions would be universal or would need to be adapted to ones genetic and environmental makeups. We performed experimental evolutionary rescue in a yeast disease model for the Wiskott–Aldrich syndrome in two genetic backgrounds and carbon sources. We found that multiple aspects of the evolutionary rescue outcome depend on the genotype, the environment, or a combination thereof. Specifically, the compensatory mutation rate and type, the molecular rescue mechanism, the genetic target, and the associated fitness cost varied across contexts. The course of compensatory evolution is therefore highly contingent on the initial conditions in which the deleterious mutation occurs. In addition, these results reveal biologically favored therapeutic targets for the Wiskott–Aldrich syndrome, including the target of an unrelated clinically approved drug. Our results experimentally illustrate the importance of epistasis and environmental evolutionary constraints that shape the adaptive landscape and evolutionary rate of molecular networks.

Microbiome investigation in the ecological speciation context of lake whitefish (Coregonus clupeaformis) using next‐generation sequencing

Few studies have applied NGS methods to investigate the microbiome of vertebrates in their natural environment and in freshwater fishes in particularly. Here, we used pyrosequencing of the 16S gene rRNA to (i) test for differences in kidney bacterial communities (i.e. microbiota) of dwarf and normal whitefish found as sympatric pairs, (ii) test the hypothesis of higher bacterial diversity in normal compared with dwarf whitefish and (iii) test for the occurrence of parallelism with the presence and composition of bacterial communities across species pairs inhabiting different lakes. The kidney microbiota of 253 dwarf and normal whitefish from five lakes was analysed combining a double‐nested PCR approach with 454 pyrosequencing. Bacteria were detected in 52.6% of the analysed whitefish. There was no overall significant difference among lakes and forms, although the lake × form interaction was found significant. We identified 579 bacterial genera, which is substantially more than previous descriptions using less sensitive techniques of fish bacterial diversity in kidney, pathogenic or not. Ten of these genera contained eighteen pathogenic species. Differences in bacteria composition between whitefish forms were not parallel among lakes. In accordance with the higher diversity of prey types, normal whitefish kidney tissue consistently had a more diverse bacterial community and this pattern was parallel among lakes. These results add to building evidence from previous studies on this system that the adaptive divergence of dwarf, and normal whitefish has been driven by both parallel and nonparallel ecological conditions across lakes.

Integrative avenues for exploring the dynamics and evolution of protein interaction networks.

Over the past decade, the study of protein interaction networks (PINs) has shed light on the organizing principles of living cells. However, PINs have been mostly mapped in one single condition. We outline three of the most promising avenues of investigation in this field, namely the study of first, how PINs are rewired by mutations and environmental perturbations; secondly, how inter-species interactions affect PIN achitectures; thirdly, what mechanisms and forces drive PIN evolution. These investigations will unravel the dynamics and condition dependence of PINs and will thus lead to a better functional annotation of network architecture. One major challenge to reach these goals is the integration of PINs with other cellular regulatory networks in the context of complex cellular phenotypes.

Feedback regulation between autophagy and PKA.

Protein kinase A (PKA) controls diverse cellular processes and homeostasis in eukaryotic cells. Many processes and substrates of PKA have been described and among them are direct regulators of autophagy. The mechanisms of PKA regulation and how they relate to autophagy remain to be fully understood. We constructed a reporter of PKA activity in yeast to identify genes affecting PKA regulation. The assay systematically measures relative protein-protein interactions between the regulatory and catalytic subunits of the PKA complex in a systematic set of genetic backgrounds. The candidate PKA regulators we identified span multiple processes and molecular functions (autophagy, methionine biosynthesis, TORC signaling, protein acetylation, and DNA repair), which themselves include processes regulated by PKA. These observations suggest the presence of many feedback loops acting through this key regulator. Many of the candidate regulators include genes involved in autophagy, suggesting that not only does PKA regulate autophagy but that autophagy also sends signals back to PKA.

Correlation of maple sap composition with bacterial and fungal communities determined by multiplex automated ribosomal intergenic spacer analysis (MARISA).

During collection, maple sap is contaminated by bacteria and fungi that subsequently colonize the tubing system. The bacterial microbiota has been more characterized than the fungal microbiota, but the impact of both components on maple sap quality remains unclear. This study focused on identifying bacterial and fungal members of maple sap and correlating microbiota composition with maple sap properties. A multiplex automated ribosomal intergenic spacer analysis (MARISA) method was developed to presumptively identify bacterial and fungal members of maple sap samples collected from 19 production sites during the tapping period. Results indicate that the fungal community of maple sap is mainly composed of yeast related to Mrakia sp., Mrakiella sp., Guehomyces pullulans, Cryptococcus victoriae and Williopsis saturnus. Mrakia, Mrakiella and Guehomyces peaks were identified in samples of all production sites and can be considered dominant and stable members of the fungal microbiota of maple sap. A multivariate analysis based on MARISA profiles and maple sap chemical composition data showed correlations between Candida sake, Janthinobacterium lividum, Williopsis sp., Leuconostoc mesenteroides, Mrakia sp., Rhodococcus sp., Pseudomonas tolaasii, G. pullulans and maple sap composition at different flow periods. This study provides new insights on the relationship between microbial community and maple sap quality.

Evolutionary biology through the lens of budding yeast comparative genomics

The budding yeast Saccharomyces cerevisiae is a highly advanced model system for studying genetics, cell biology and systems biology. Over the past decade, the application of high-throughput sequencing technologies to this species has contributed to this yeast also becoming an important model for evolutionary genomics. Indeed, comparative genomic analyses of laboratory, wild and domesticated yeast populations are providing unprecedented detail about many of the processes that govern evolution, including long-term processes, such as reproductive isolation and speciation, and short-term processes, such as adaptation to natural and domestication-related environments.