Biology subjects

Tremblay, J.

Publications and source records attributed to Tremblay, J..

33 records · Page 2Linked to original sources

bioRxiv2022

Plants release miRNAs in the rhizosphere, targeting microbial genes

Recently, small RNAs have been shown to play important roles in cross-kingdom communication, notably in plant-pathogen relationships. Plant miRNAs were even shown to regulate gene expression in the gut microbiota. But what impact do they have on the plant microbiota? Here we hypothesized that plant miRNAs can be found in the rhizosphere of plants, where they are taken up by rhizosphere bacteria, influencing their gene expression, thereby shaping the rhizosphere bacterial community. We found plant miRNAs in the rhizosphere of Arabidopsis thaliana and Brachypodium distachyon. These plant miRNAs were also found in rhizosphere bacteria, and fluorescent synthetic miRNAs were taken up by cultivated bacteria. A mixture of five plant miRNAs modulated the expression of more than a hundred genes in Variovorax paradoxus, whereas no effect was observed in Bacillus mycoides. Similarly, when V. paradoxus was grown in the rhizosphere of Arabidopsis that overexpressed a miRNA, it changed its gene expression profile. The rhizosphere bacterial communities of Arabidopsis mutants that were impaired in their miRNA or small RNA pathways differed from wildtype plants. Similarly, bacterial communities of Arabidopsis overexpressing specific miRNAs diverged from control plants. Finally, the growth and the abundance of specific ASVs of a simplified soil community were affected by exposure to a mixture of synthetic plant miRNAs. Taken together, our results support a paradigm shift in plant-bacteria interactions in the rhizosphere, adding miRNAs to the plant tools shaping microbial assembly.

plant biology↗

bioRxiv2022

High resolution shotgun metagenomics: the more data, the better?

In shotgun metagenomics (SM), the state of the art bioinformatic workflows are referred to as high resolution shotgun metagenomics (HRSM) and require intensive computing and disk storage resources. While the increase in data output of the latest iteration of high throughput DNA sequencing systems can allow for unprecedented sequencing depth at a minimal cost, adjustments in HRSM workflows will be needed to properly process these ever-increasing sequence datasets. One potential adaptation is to generate so-called shallow SM datasets that contain fewer sequencing data per sample as compared to the more classic high coverage sequencing. While shallow sequencing is a promising avenue for SM data analysis, detailed benchmarks using real data are lacking. In this case study, we took four public SM datasets, one massive and the others moderate in size and subsampled each dataset at various levels to mimic shallow sequencing datasets of various sequencing depths. Our results suggest that shallow SM sequencing is a viable avenue to obtain sound results regarding microbial community structures and that high depth sequencing does not bring additional elements for ecological interpretation. More specifically, results obtained by subsampling as little as 0.5M sequencing clusters per sample were similar to the results obtained with the largest subsampled dataset for the human gut and agricultural soil datasets. For the Antarctic dataset, which contained only a few samples, 4M sequencing clusters per sample was found to generate comparable results to the full dataset. One area where ultra-deep sequencing and maximizing the usage of all data was undeniably beneficial was in the generation of metagenome-assembled genomes (MAGs). Key points- Three public multi-sample shotgun metagenomic NovaSeq datasets totalling 12,389,583 and 202 Gb, respectively were analyzed at various sequencing depths to evaluate the accuracy of shallow shotgun metagenomic sequencing using a high resolution shotgun metagenomic bioinformatic workflow. A synthetic mock community of 20 bacterial genomes was also analyzed for validation purposes. - Datasets subsampled to low sequencing depths gave nearly identical ecological patterns (taxonomic and functional composition and beta-alpha-diversity) compared to high depth subsampled datasets. - Rare taxa and functions could be uncovered with high sequencing depth vs. low sequencing depth datasets, but did not affect global ecological patterns. - High sequencing depth was positively correlated with both quantity and quality of recovered metagenome-assembled genomes.

bioinformatics↗

bioRxiv2022

Use of Fe3O4 nanoparticles in reactor co-digestion of residues from 1G2G ethanol biorefinery: microbiological routes and operational aspects

The co-digestion of residues from the sugarcane industry has already proven to be a highly attractive process for biogas production through anaerobic digestion (AD). The use of residues such as vinasse (1G) filter cake (1G) and deacetylation liquor (2G) in CSTR operation showed the potential for integrating 1G and 2G ethanol biorefineries through AD in previous work by our research group. The use of nanoparticles (NP) is a favorable way to optimize AD processes, as these additives allow the introduction of nutrients to the process more assertively concerning the distribution and interaction with microorganisms. The present work proposed the optimization of the co-digestion of vinasse, filter cake, and deacetylation liquor in a continuous reactor by adding Fe3O4 NP, comparing the results with a previous reactor operation without NP. Initially, tests were carried out in batches with different NP concentrations, resulting in 5 mg L-1 as the best concentration to be added in the continuous reactor along the increments of the applied organic rate load (ORL). CH4 production reached a maximum value of 2.8 {+/-} 0.1 NLCH4 gVS-1 and the organic matter removal reached 71 {+/-} 0.9%, in phase VI (ORL of 5.5 gVS L-1 day-1). This production was 90% higher than the reactor co-digestion operation without NP. The pH and alkalinity results indicated the methanogenesis stabilization within 60 days of operation: 30 days before when there was no NP added. The AD development was stable, presenting low variations in the oxidation-reduction potential (ORP) and stable organic acid (OA) concentrations, which indicated the propionic acid route to produce CH4 was predominant. The main methanogenic Archeae identified was Methanoculleus, indicating that the predominant metabolic route was that of acetate (SAO) coupled with hydrogenotrophic methanogenesis. The use of Fe3O4 NP managed to improve the AD from the 1G2G ethanol production residues and stimulated the microbial community growth, not modifying the preferable metabolic pathways.

bioengineering↗

bioRxiv2022

Hidden potential of the supporting scaffold as a structural module for plant cystatin design

Protein engineering approaches have been proposed to improve the inhibitory properties of plant cystatins towards herbivorous pest digestive Cys proteases, typically involving sequence alterations in the inhibitory loops and/or N-terminal trunk of the protein interacting with specific amino acid residues of the target protease. In this study, we assessed whether the loops-supporting frame, or scaffold, would represent a valuable structural module for cystatin function improvement. Twenty hybrid cystatins were designed in silico, consisting of the N-terminal trunk and two inhibitory loops of a given donor cystatin grafted onto the scaffold of an alternative, recipient cystatin. Synthetic genes for the hybrids were expressed in E. coli, and the resulting proteins assessed for their potency to inhibit model Cys protease papain and the digestive Cys proteases of Colorado potato beetle (Leptinotarsa decemlineata) used as an insect pest model. In line with the occurrence of positively selected amino acids presumably influencing inhibitory activity in the scaffold region of plant cystatins, grafting the N-terminal trunk and inhibitory loops of a given cystatin onto the scaffold of an alternative cystatin generally had an effect on the inhibitory potency of these function-related elements against Cys proteases. For instance, hybrid cystatins including the three structural elements of model tomato cystatin SlCYS8 grafted on the scaffold of cystatins from other plant families showed Ki values altered by up to 3-fold for papain, and inhibitory efficiencies increased by up to 8-fold against L. decemlineata cathepsin L-like proteases, compared to wild-type SlCYS8 bearing the original scaffold. Our data point to a significant influence of the cystatin scaffold on the inhibitory activity of the N-terminal trunk and protease inhibitory loops. They also suggest the potential of this structural element as a module for plant cystatin design to generate functional variability against Cys proteases, including the digestive proteases of herbivorous pests.

plant biology↗

bioRxiv2021

Animal soil food web complexity triggers shifts in microbial communities, including PAH degraders, but without clear effects on phenanthrene phytoremediation

The aim of this study was to determine whether the complexity of the animal soil food web (SFWC) is a significant factor influencing the soil microbial communities, the productivity of the willow, and the degradation rates of 100 mg kg-1 phenanthrene contamination. The SFWC treatment had eight levels: just the microbial community (BF), or the BF with nematodes (N), springtails (C), earthworms (E), CE, CN, EN, CEN. After eight weeks of growth, the height and biomass of willows were significantly affected by the SFWC, whereas the amount of phenanthrene degraded was not affected, reaching over 95% in all pots. SFWC affected the structure and the composition of the bacterial, archaeal and fungal communities, with significant effects of SFWC on the relative abundance of fungal genera such as Sphaerosporella, a known willow symbiont during phytoremediation, and bacterial phyla such as Actinobacteriota, containing many PAH degraders. These SFWC effects on microbial communities were not clearly reflected in the community structure and abundance of PAH degraders, even though some degraders related to the Actinobacteriota and the diversity of Gram-negative degraders were affected by the SFWC treatments. Overall, our results suggest that, under our experimental conditions, SFWC does not affect significantly willow phytoremediation outcomes. ImportancePolycyclic aromatic hydrocarbons (PAH) pose a threat to soil ecosystems. Phytoremediation is a green technology that can help restore ecosystems health affected by PAH contamination. Past research on phytoremediation of PAH has focused on the roles of plant and microbes in contaminant fates. However, soil environments usually harbor large faunal communities that interact with both the plant and the microbial communities, potentially altering the phytoremediation process. We hypothesized that soil food web complexity (SFWC), represented by increasing levels of soil fauna, influences PAH degradation through interactions with the plant and the microbes. In this study, we demonstrated that SFWC increases the plant biomass and changes the composition of the microbial community, especially the fungal structure. In our pot experiment, more complex levels of SFWC did not contribute to higher degradation rates, but the increased plant biomass and the higher relative abundance of fungal genera associated with lower plant stress could indirectly contribute to better phytoremediation outcomes. Our results highlight the importance of considering the contributions of soil fauna to the success of phytoremediation.

microbiology↗

bioRxiv2021

Harnessing the functional diversity of plant cystatins to design inhibitor variants highly active against herbivorous arthropod digestive proteases

Protein engineering approaches have been proposed to improve the inhibitory properties of plant cystatins against herbivorous arthropod digestive proteases. These approaches typically involve the site-directed mutagenesis of functionally relevant amino acids, the production and selection of improved inhibitory variants by molecular phage display procedures, or the design of bi/multifunctional translational fusions integrating one or several cystatin inhibitory domains. Here, we propose a new approach where the function-related structural elements of a cystatin are substituted by the corresponding elements of an alternative cystatin. Cys protease inhibitory assays were first performed with 20 representative plant cystatins and model Cys proteases, including herbivorous arthropod digestive proteases, to appreciate the extent of functional variability among plant cystatin protein family members. The most, and less, potent of these cystatins were then used as donors of structural elements to create hybrids of tomato cystatin SlCYS8 used as a model recipient inhibitor. Our data confirm the wide variety of cystatin protease inhibitory profiles among plant taxa. They also demonstrate the usefulness of these proteins as a pool of discrete structural elements for the design of cystatin variants with improved potency against herbivorous pest digestive Cys proteases.

plant biology↗

bioRxiv2021

Critical Assessment of Metagenome Interpretation - the second round of challenges

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the community-driven initiative for the Critical Assessment of Metagenome Interpretation (CAMI). In its second challenge, CAMI engaged the community to assess their methods on realistic and complex metagenomic datasets with long and short reads, created from [~]1,700 novel and known microbial genomes, as well as [~]600 novel plasmids and viruses. Altogether 5,002 results by 76 program versions were analyzed, representing a 22x increase in results. Substantial improvements were seen in metagenome assembly, some due to using long-read data. The presence of related strains still was challenging for assembly and genome binning, as was assembly quality for the latter. Taxon profilers demonstrated a marked maturation, with taxon profilers and binners excelling at higher bacterial taxonomic ranks, but underperforming for viruses and archaea. Assessment of clinical pathogen detection techniques revealed a need to improve reproducibility. Analysis of program runtimes and memory usage identified highly efficient programs, including some top performers with other metrics. The CAMI II results identify current challenges, but also guide researchers in selecting methods for specific analyses.

bioinformatics↗

bioRxiv2021

Relative and quantitative rhizosphere microbiome profiling result in distinct abundance patterns

Next-generation sequencing is recognized as one of the most popular and cost-effective way of characterizing microbiome in multiple samples. However, most of the currently available amplicon sequencing approaches are inherently limited, as they are often presented based on the relative abundance of microbial taxa, which may not fully represent actual microbiome profiles. Here, we combined amplicon sequencing (16S rRNA gene for bacteria and ITS region for fungi) with real-time quantitative PCR (qPCR) to characterize the rhizosphere microbiome of wheat. We show that the increase in relative abundance of major microbial phyla does not necessarily result in an increase in abundance. One striking observation when comparing relative and quantitative abundances was a substantial increase in the abundance of almost all phyla associated with the rhizosphere of plants grown in soil with no history of water stress as compared with the rhizosphere of plants growing in soil with a history of water stress, which was in contradiction with the trends observed in the relative abundance data. Our results suggest that the estimated absolute abundance approach gives a different perspective than the relative abundance approach, providing complementary information that helps to better understand the rhizosphere microbiome.

ecology↗

bioRxiv2020

LIONirs: flexible Matlab toolbox for fNIRS data analysis.

BackgroundFunctional near-infrared spectroscopy (fNIRS) is a suitable tool for recording brain function in pediatric or challenging populations. As with other neuroimaging techniques, the scientific community is engaged in an evolving debate regarding the most adequate methods for performing fNIRS data analyses. New methodWe introduce LIONirs, a neuroinformatics toolbox for fNIRS data analysis, designed to follow two main goals: (1) flexibility, to explore several methods in parallel and verify results using 3D visualization; (2) simplicity, to apply a defined processing pipeline to a large dataset of subjects by using the MATLAB Batch System. ResultsWithin the graphical user interfaces (DisplayGUI), the user can reject noisy intervals and correct artifacts, while visualizing the topographical projection of the data onto the 3D head representation. Data decomposition methods are available for the identification of relevant signatures, such as brain responses or artifacts. Multimodal data recorded simultaneously to fNIRS, such as physiology, electroencephalography or audio-video, can be visualized using the DisplayGUI. The toolbox includes several functions that allow one to read, preprocess, and analyze fNIRS data, including task-based and functional connectivity measures. Comparison with existing methodsSeveral good neuroinformatics tools for fNIRS data analysis are currently available. None of them emphasize multimodal visualization of the data throughout the preprocessing steps and multidimensional decomposition, which are essential for understanding challenging data. Furthermore, LIONirs provides compatibility and complementarity with other existing tools by supporting common data format. ConclusionsLIONirs offers a flexible platform for basic and advanced fNIRS data analysis, shown through real experimental examples. HighlightsO_LIThe LIONirs toolbox is designed for fNIRS data inspection and visualization. C_LIO_LIMethods are integrated for isolation of relevant activity and correction of artifacts. C_LIO_LIMultimodal auxiliary, EEG or audio-video are visualized alongside the fNIRS data. C_LIO_LITask-based and functional connectivity measure analysis tools are available. C_LIO_LIThe code structure allows to automated and standardized analysis of large data set. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/257634v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@9cced8org.highwire.dtl.DTLVardef@cfdcc3org.highwire.dtl.DTLVardef@a694fcorg.highwire.dtl.DTLVardef@7f35f4_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

Soil characteristics constrain the response of bacterial and fungal communities and hydrocarbon degradation genes to phenanthrene soil contamination and phytoremediation with poplars

Rhizodegradation is a promising cleanup technology where microorganisms degrade soil contaminants in the rhizosphere. A symbiotic relationship is expected to occur between plant roots and soil microorganisms in contaminated soils that enhance natural microbial degradation in soils. However, little is known about how this initial microbiota influences the rhizodegradation outcome in a context of different soil microbiotas. Recent studies have hinted that soil initial diversity has a determining effect on the outcome of contaminant degradation. To test this hypothesis, we planted (P) or not (NP) balsam poplars (Populus balsamifera) in two soils of contrasting diversity (agricultural and forest) that were contaminated or not with 50 mg kg-1 of phenanthrene (PHE). The DNA from the rhizosphere of the P and the bulk soil of the NP pots was extracted and the bacterial genes encoding for the 16S rRNA, the PAH ring-hydroxylating dioxygenase alpha subunits (PAH-RHD) of gram-positive (GP) and gram-negative (GN) bacteria, and the fungal ITS region were sequenced to characterize the microbial communities. and the abundance of the PAH-RHD genes were also quantified by real-time quantitative PCR. Plant presence had a significant effect on PHE degradation only in the forest soil, whereas both NP and P agricultural soils degraded the same amount of PHE. Bacterial communities were principally affected by the soil type, and upon contamination the dominant PAH degrading community was similarly constrained by soil type. Our results highlight the crucial importance of soil microbial and physicochemical characteristics in the outcome of rhizoremediation.

microbiology↗

bioRxiv2019

Parallel Factor Analysis (PARAFAC) for multidimensional decomposition of fNIRS data - A validation study

SignificanceCurrent techniques for data analysis in functional near-infrared spectroscopy (fNIRS), such as artifact correction, do not allow to integrate the information originating from both wavelengths, considering only temporal and spatial dimensions of the signals structure. Parallel factor analysis (PARAFAC) has previously been validated as a multidimensional decomposition technique in other neuroimaging fields. AimWe aimed to introduce and validate the use of PARAFAC for the analysis of fNIRS data, which is inherently multidimensional (time, space, wavelength). ApproachWe used data acquired in 17 healthy adults during a verbal fluency task to compare the efficacy of PARAFAC for motion artifact correction to traditional 2D decomposition techniques, i.e. target principal (tPCA) and independent component analysis (ICA). Correction performance was further evaluated under controlled conditions with simulated artifacts and hemodynamic response functions. ResultsPARAFAC achieved significantly higher improvement in data quality as compared to tPCA and ICA. Correction in several simulated signals further validated its use and promoted it as a robust method independent of the artifacts characteristics. ConclusionsThis study describes the first implementation of PARAFAC in fNIRS and provides validation for its use to correct artifacts. PARAFAC is a promising data-driven alternative for multidimensional data analyses in fNIRS and this study paves the way for further applications.

neuroscience↗

bioRxiv2019

Impact of early childhood malnutrition on the adult brain function: an ERP study

According to the World Health Organization, 45% of deaths among children under five years of age are caused by malnutrition, which impacts more than 224 million children globally. The Barbados Nutrition Study (BNS) is a 50+ year longitudinal study on a Barbadian cohort with histories of moderate to severe protein-energy malnutrition (PEM) limited to the first year of life and a healthy comparison group. We have previously used quantitative electroencephalography (EEG) to highlight differences in brain function during childhood (lower alpha1 activity and higher theta, alpha2 and beta activity) between participants who suffered from early PEM and controls. In order to determine whether similar differences between the PEM and control groups persisted into adulthood, our current study used recordings obtained during a Go-No-Go task in a subsample of the original BNS cohort (N=53) at ages 45-51 years. We found that previously malnourished adults (n=24) had a higher rate of omission errors on the task relative to controls (n=29). Evoked-Related Potentials (ERP) were significantly different in participants with histories of early PEM, who presented with lower N2 amplitudes (p<0.05). These findings are typically associated with impaired conflict monitoring and/or attention deficits and may therefore be linked to the attentional and executive function deficits that have been previously reported in this cohort in childhood and again in middle-adulthood. HighlightsO_LIChildhood malnutrition increases risk of brain function alterations. C_LIO_LIThere is a need to investigate the evolution of those outcomes later in life. C_LIO_LIAdults who suffered childhood malnutrition undertook a Go-No-Go task during EEG. C_LIO_LITask performance and N2 amplitude were reduced in malnutrition group (vs control). C_LIO_LIFirst evidence of adult brain function alteration following childhood malnutrition. C_LI

neuroscience↗

bioRxiv2018

Nitrogen- and phosphorus-starved Triticum aestivum show distinct belowground microbiome profiles

Many plants have natural partnerships with microbes that can boost their nitrogen (N) and/or phosphorus (P) acquisition. To assess whether wheat may have undiscovered associations of these types, we tested if N/P-starved Triticum aestivum show microbiome profiles that are simultaneously different from those of N/P-amended plants and those of their own bulk soils. The bacterial and fungal communities of root, rhizosphere, and bulk soil samples from the Historical Dryland Plots (Lethbridge, Canada), which hold T. aestivum that is grown both under N/P fertilization and in conditions of extreme N/P-starvation, were taxonomically described and compared (bacterial 16S rRNA genes and fungal Internal Transcribed Spacers - ITS). As the list may include novel N- and/or P-providing wheat partners, we then identified all the operational taxonomic units (OTUs) that were proportionally enriched in one or more of the nutrient starvation- and plant-specific communities. These analyses revealed: a) distinct N-starvation root and rhizosphere bacterial communities that were proportionally enriched, among others, in OTUs belonging to families Enterobacteriaceae, Chitinophagaceae, Comamonadaceae, Caulobacteraceae, Cytophagaceae, Streptomycetaceae, b) distinct N-starvation root fungal communities that were proportionally enriched in OTUs belonging to taxa Lulworthia, Sordariomycetes, Apodus, Conocybe, Ascomycota, Crocicreas, c) a distinct P-starvation rhizosphere bacterial community that was proportionally enriched in an OTU belonging to genus Agrobacterium, and d) a distinct P-starvation root fungal community that was proportionally enriched in OTUs belonging to genera Parastagonospora and Phaeosphaeriopsis. Our study might have exposed wheat-microbe connections that can form the basis of novel complementary yield-boosting tools.

microbiology↗

bioRxiv2018

GenPipes: an open-source framework for distributed and scalable genomic analyses

With the decreasing cost of sequencing and the rapid developments in genomics technologies and protocols, the need for validated bioinformatics software that enables efficient large-scale data processing is growing. Here we present GenPipes, a flexible Python-based framework that facilitates the development and deployment of multi-step workflows optimized for High Performance Computing clusters and the cloud. GenPipes already implements 12 validated and scalable pipelines for various genomics applications, including RNA-Seq, ChIP-Seq, DNA-Seq, Methyl-Seq, Hi-C, capture Hi-C, metagenomics and PacBio long read assembly. The software is available under a GPLv3 open source license and is continuously updated to follow recent advances in genomics and bioinformatics. The framework has been already configured on several servers and a docker image is also available to facilitate additional installations. In summary, GenPipes offers genomic researchers a simple method to analyze different types of data, customizable to their needs and resources, as well as the flexibility to create their own workflows.

bioinformatics↗

bioRxiv2018

Assessing precocious maturation in salmon using ultrasound imaging

AO_SCPLOWBSTRACTC_SCPLOWSalmonids are characterized by a large diversity of life histories, but their study is often limited by the imperfect observation of the true state of an individual in the wild. Challenged by the need to reduce uncertainty of empirical data, recent development in medical imaging techniques offered new opportunities to assess precocious maturation in Atlantic salmon parr. Traditional phenotypic (external) examination and ultrasound (internal) examination were compared and recommendations on fish handling and ultrasound image interpretation are provided. By allowing to see the unseen, portable ultrasound imaging offers great opportunities for ecological studies in the wild, such as the assessment of individual sexual maturation.

ecology↗