Honeybee gut bacterial strain improved survival and gut microbiota homeostasis in Apis mellifera exposed in vivo to clothianidin.

Pesticides are causing honeybee mortality worldwide. Research carried out on honeybees indicates that application of pesticides has a significant impact on the core gut community, which ultimately leads to an increase in the growth of harmful pathogens. Disturbances caused by pesticides also affect the way bacterial members interact, which results in gut microbial dysbiosis. Administration of beneficial microbes has been previously demonstrated to be effective in treating or preventing disease in honeybees. The objective of this study was to measure under in vivo conditions the ability of two bacterial strains (the Enterobacter sp. and Pantoea sp.) isolated from honeybee gut to improve survival and mitigate gut microbiota dysbiosis in honeybees exposed to a sublethal clothianidin dose (0.1 ppb). Both gut bacterial strains were selected for their ability to degrade clothianidin in vitro regardless of their host-microbe interaction characteristics (e.g., beneficial, neutral, or harmful). To this end, we conducted cage trials on 4- to 6-day-old newly emerging honeybees. During microbial administration, we jointly monitored the taxonomic distribution and activity level of bacterial symbionts quantifying 16S rRNA transcripts. First, curative administration of the Pantoea sp. strain significantly improved the survival of clothianidin-exposed honeybees compared to sugar control bees (i.e., supplemented with sugar [1:1]). Second, curative administration of the Enterobacter sp. strain significantly mitigated the clothianidin-induced dysbiosis observed in the midgut structural network, but without improving survival. IMPORTANCE: The present work suggests that administration of bacterial strains isolated from honeybee gut may promote recovery of gut microbiota homeostasis after prolonged clothianidin exposure, while improving survival. This study highlights that gut bacterial strains hold promise for developing efficient microbial formulations to mitigate environmental pesticide exposure in honeybee colonies.

Evolution and host-specific adaptation of Pseudomonas aeruginosa.

The major human bacterial pathogen Pseudomonas aeruginosa causes 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 of P. aeruginosa and highlight the importance of global surveillance and cross-infection prevention in averting the emergence of future epidemic clones.

Complete genome sequence of multidrug-resistant Enterobacter roggenkampii 0-E.

Here, we present the complete 4.77 Mb genome of Enterobacter roggenkampii 0-E assembled with Oxford Nanopore long reads. This genome harbors 19 antimicrobial resistance genes, including ramA and marA decreasing permeability to carbapenems. This genome adds novel knowledge on emerging multidrug resistance in the Enterobacter cloacae species complex.

Characterization of gill bacterial microbiota in wild Arctic char (Salvelinus alpinus) across lakes, rivers, and bays in the Canadian Arctic ecosystems.

Teleost gill mucus has a highly diverse microbiota, which plays an essential role in the host's fitness and is greatly influenced by the environment. Arctic char (Salvelinus alpinus), a salmonid well adapted to northern conditions, faces multiple stressors in the Arctic, including water chemistry modifications, that could negatively impact the gill microbiota dynamics related to the host's health. In the context of increasing environmental disturbances, we aimed to characterize the taxonomic distribution of transcriptionally active taxa within the bacterial gill microbiota of Arctic char in the Canadian Arctic in order to identify active bacterial composition that correlates with environmental factors. For this purpose, a total of 140 adult anadromous individuals were collected from rivers, lakes, and bays belonging to five Inuit communities located in four distinct hydrologic basins in the Canadian Arctic (Nunavut and Nunavik) during spring (May) and autumn (August). Various environmental factors were collected, including latitudes, water and air temperatures, oxygen concentration, pH, dissolved organic carbon (DOC), salinity, and chlorophyll-a concentration. The taxonomic distribution of transcriptionally active taxa within the gill microbiota was quantified by 16S rRNA gene transcripts sequencing. The results showed differential bacterial activity between the different geographical locations, explained by latitude, salinity, and, to a lesser extent, air temperature. Network analysis allowed the detection of a potential dysbiosis signature (i.e., bacterial imbalance) in fish gill microbiota from Duquet Lake in the Hudson Strait and the system Five Mile Inlet connected to the Hudson Bay, both showing the lowest alpha diversity and connectivity between taxa.IMPORTANCEThis paper aims to decipher the complex relationship between Arctic char (Salvelinus alpinus) and its symbiotic microbial consortium in gills. This salmonid is widespread in the Canadian Arctic and is the main protein and polyunsaturated fatty acids source for Inuit people. The influence of environmental parameters on gill microbiota in wild populations remains poorly understood. However, assessing the Arctic char's active gill bacterial community is essential to look for potential pathogens or dysbiosis that could threaten wild populations. Here, we concluded that Arctic char gill microbiota was mainly influenced by latitude and air temperature, the latter being correlated with water temperature. In addition, a dysbiosis signature detected in gill microbiota was potentially associated with poor fish health status recorded in these disturbed environments. With those results, we hypothesized that rapid climate change and increasing anthropic activities in the Arctic might profoundly disturb Arctic char gill microbiota, affecting their survival.

Mitochondrial genome sequence of the protist Ancyromonas sigmoides Kent, 1881 (Ancyromonadida) from the Sugluk Inlet, Hudson Strait, Nunavik, Québec.

Introduction: There is little information on evolutionarily ancient eukaryotes, which are often referred to as basal eukaryotes, in Arctic waters. Despite earlier studies being conducted in the Russian White Sea, only few have been reported. Methods: Following a shotgun sequence survey of diatom cultures from Sugluk Inlet off the Hudson Strait in Northern Québec, we obtained the complete mitochondrial genome and the operon of nuclear ribosomal RNA genes from a strain that matches that of Ancyromonas sigmoides (Kent, 1881). Results: The sequence of the mitogenome retrieved was 41,889 bp in length and encoded 38 protein-coding genes, 5 non-conserved open-reading frames, and 2 rRNA and 24 tRNA genes. The mitogenome has retained sdh2 and sdh3, two genes of the succinate dehydrogenase complex, which are sometimes found among basal eukaryotes but seemingly missing among the Malawimonadidae, a lineage sister to Ancyromonadida in some phylogenies. The phylogeny inferred from the 18S rRNA gene associated A. sigmoides from Sugluk Inlet with several other strains originating from the Arctic. The study also unveiled the presence of a metagenomic sequence ascribed to bacteria in GenBank, but it was clearly a mitochondrial genome with a gene content highly similar to that of A. sigmoides, including the non-conserved open-reading frames. Discussion: After re-annotation, a phylogeny was inferred from mitochondrial protein sequences, and it strongly associated A. sigmoides with the misidentified organism, with the two being possibly conspecific or sibling species as they are more similar to one another than to species of the genus Malawimonas. Overall our phylogeny showed that the ice associated ancryomonads were clearly distinct from more southerly strains.

Draft genome sequences of six Pseudomonas spp. and one Rheinheimera sp. isolated from oil sands process-affected water from Alberta, Canada.

We report the draft genomes of seven bacterial strains (six Pseudomonas spp. and one Rheinheimera sp.) isolated from environmental water samples from oil sands tailings ponds that have accumulated a wide variety of organic compounds, salts and metals.

Complete genome sequence of Pseudomonas veronii strain OST1911 isolated from oil sand tailing pond water in Alberta, Canada.

Here, we report the complete genome sequence of Pseudomonas veronii strain OST1911, recovered from oil sand process-affected water accumulated in tailing ponds. This water contains numerous organic and inorganic compounds of environmental significance. The genome size is 6,435,955 bp with a G+C content of 61.21%.

Rapid on-site detection of harmful algal blooms: real-time cyanobacteria identification using Oxford Nanopore sequencing.

With the increasing occurrence and severity of cyanobacterial harmful algal blooms (cHAB) at the global scale, there is an urgent need for rapid, accurate, accessible, and cost-effective detection tools. Here, we detail the RosHAB workflow, an innovative, in-the-field applicable genomics approach for real-time, early detection of cHAB outbreaks. We present how the proposed workflow offers consistent taxonomic identification of water samples in comparison to traditional microscopic analyses in a few hours and discuss how the generated data can be used to deepen our understanding on cyanobacteria ecology and forecast HABs events. In parallel, processed water samples will be used to iteratively build the International cyanobacterial toxin database (ICYATOX; http://icyatox.ibis.ulaval.ca) containing the analysis of novel cyanobacterial genomes, including phenomics and genomics metadata. Ultimately, RosHAB will (1) improve the accuracy of on-site rapid diagnostics, (2) standardize genomic procedures in the field, (3) facilitate these genomics procedures for non-scientific personnel, and (4) identify prognostic markers for evidence-based decisions in HABs surveillance.

Draft genome sequences of six bacterial strains isolated from Cannabis rhizosphere soil.

Although bacterial isolates from Cannabis flowers were reported and sequenced, few from its rhizosphere have been characterized. Here we report the draft genomes of six bacterial strains isolated from Cannabis rhizosphere soil samples. These sequences may shed light on plant-microbe interactions in the Cannabis rhizosphere at the molecular level.

Draft genome sequence of Pseudomonas sp. ER28, a cyclohexane pentanoic acid degrader isolated from oil sands process-affected water from Alberta, Canada.

We report the draft genome sequence of Pseudomonas sp. ER28, capable of utilizing the model naphthenic acid, cyclohexane pentanoic acid, as its sole carbon source. It was recovered from oil sands process-affected water containing cyclic and acyclic naphthenic acids. The genome size is 5.7 Mbp, and the G + C content is 60%.

Genetic diversity of Salmonella enterica isolated over 13 years from raw California almonds and from an almond orchard.

A comparative genomic analysis was conducted for 171 Salmonella isolates recovered from raw inshell almonds and raw almond kernels between 2001 and 2013 and for 30 Salmonella Enteritidis phage type (PT) 30 isolates recovered between 2001 and 2006 from a 2001 salmonellosis outbreak-associated almond orchard. Whole genome sequencing was used to measure the genetic distance among isolates by single nucleotide polymorphism (SNP) analyses and to predict the presence of plasmid DNA and of antimicrobial resistance (AMR) and virulence genes. Isolates were classified by serovars with Parsnp, a fast core-genome multi aligner, before being analyzed with the CFSAN SNP Pipeline (U.S. Food and Drug Administration Center for Food Safety and Applied Nutrition). Genetically similar (≤18 SNPs) Salmonella isolates were identified among several serovars isolated years apart. Almond isolates of Salmonella Montevideo (2001 to 2013) and Salmonella Newport (2003 to 2010) differed by ≤9 SNPs. Salmonella Enteritidis PT 30 isolated between 2001 and 2013 from survey, orchard, outbreak, and clinical samples differed by ≤18 SNPs. One to seven plasmids were found in 106 (62%) of the Salmonella isolates. Of the 27 plasmid families that were identified, IncFII and IncFIB plasmids were the most predominant. AMR genes were identified in 16 (9%) of the survey isolates and were plasmid encoded in 11 of 16 cases; 12 isolates (7%) had putative resistance to at least one antibiotic in three or more drug classes. A total of 303 virulence genes were detected among the assembled genomes; a plasmid that harbored a combination of pef, rck, and spv virulence genes was identified in 23% of the isolates. These data provide evidence of long-term survival (years) of Salmonella in agricultural environments.

Complete genome sequences of agricultural azole-resistant Penicillium rubens encoding CYP51A and ERG11 paralogues.

Azoles are major antifungals in agriculture and medicine. However, the surge of intrinsic azole resistance is critical for public health. Here, we present the complete long-read sequencing of three azole-resistant Penicillium rubens from food crops. The presence of CYP51A and ERG11 paralogues was confirmed, as in other azole-resistant P. rubens.

Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation.

Introduction: Persistent symptoms after COVID-19 infection ("long COVID") negatively affects almost half of COVID-19 survivors. Despite its prevalence, its pathophysiology is poorly understood, with multiple host systems likely affected. Here, we followed patients from hospital to discharge and used a systems-biology approach to identify mechanisms of long COVID. Methods: RNA-seq was performed on whole blood collected early in hospital and 4-12 weeks after discharge from 24 adult COVID-19 patients (10 reported post-COVID symptoms after discharge). Differential gene expression analysis, pathway enrichment, and machine learning methods were used to identify underlying mechanisms for post-COVID symptom development. Results: Compared to patients with post-COVID symptoms, patients without post-COVID symptoms had larger temporal gene expression changes associated with downregulation of inflammatory and coagulation genes over time. Patients could also be separated into three patient endotypes with differing mechanistic trajectories, which was validated in another published patient cohort. The "Resolved" endotype (lowest rate of post-COVID symptoms) had robust inflammatory and hemostatic responses in hospital that resolved after discharge. Conversely, the inflammatory/hemostatic responses of "Suppressive" and "Unresolved" endotypes (higher rates of patients with post-COVID symptoms) were persistently dampened and activated, respectively. These endotypes were accurately defined by specific blood gene expression signatures (6-7 genes) for potential clinical stratification. Discussion: This study allowed analysis of long COVID whole blood transcriptomics trajectories while accounting for the issue of patient heterogeneity. Two of the three identified and externally validated endotypes ("Unresolved" and "Suppressive") were associated with higher rates of post-COVID symptoms and either persistently activated or suppressed inflammation and coagulation processes. Gene biomarkers in blood could potentially be used clinically to stratify patients into different endotypes, paving the way for personalized long COVID treatment.

Predicting severity in COVID-19 disease using sepsis blood gene expression signatures.

Severely-afflicted COVID-19 patients can exhibit disease manifestations representative of sepsis, including acute respiratory distress syndrome and multiple organ failure. We hypothesized that diagnostic tools used in managing all-cause sepsis, such as clinical criteria, biomarkers, and gene expression signatures, should extend to COVID-19 patients. Here we analyzed the whole blood transcriptome of 124 early (1-5 days post-hospital admission) and late (6-20 days post-admission) sampled patients with confirmed COVID-19 infections from hospitals in Quebec, Canada. Mechanisms associated with COVID-19 severity were identified between severity groups (ranging from mild disease to the requirement for mechanical ventilation and mortality), and established sepsis signatures were assessed for dysregulation. Specifically, gene expression signatures representing pathophysiological events, namely cellular reprogramming, organ dysfunction, and mortality, were significantly enriched and predictive of severity and lethality in COVID-19 patients. Mechanistic endotypes reflective of distinct sepsis aetiologies and therapeutic opportunities were also identified in subsets of patients, enabling prediction of potentially-effective repurposed drugs. The expression of sepsis gene expression signatures in severely-afflicted COVID-19 patients indicates that these patients should be classified as having severe sepsis. Accordingly, in severe COVID-19 patients, these signatures should be strongly considered for the mechanistic characterization, diagnosis, and guidance of treatment using repurposed drugs.

Genome evolution drives transcriptomic and phenotypic adaptation in Pseudomonas aeruginosa during 20 years of infection.

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.

Dietary Contamination with a Neonicotinoid (Clothianidin) Gradient Triggers Specific Dysbiosis Signatures of Microbiota Activity along the Honeybee (Apis mellifera) Digestive Tract.

Pesticides are increasing honeybee (Apis mellifera) death rates globally. Clothianidin neonicotinoid appears to impair the microbe-immunity axis. We conducted cage experiments on newly emerged bees that were 4-6 days old and used a 16S rRNA metataxonomic approach to measure the impact of three sublethal clothianidin concentrations (0.1, 1 and 10 ppb) on survival, sucrose syrup consumption and gut microbiota community structure. Exposure to clothianidin significantly increased mortality in the three concentrations compared to controls. Interestingly, the lowest clothianidin concentration was associated with the highest mortality, and the medium concentration with the highest food intake. Exposure to clothianidin induced significant variation in the taxonomic distribution of gut microbiota activity. Co-abundance network analysis revealed local dysbiosis signatures specific to each gut section (midgut, ileum and rectum) were driven by specific taxa. Our findings confirm that exposure to clothianidin triggers a reshuffling of beneficial strains and/or potentially pathogenic taxa within the gut, suggesting a honeybee's symbiotic defense systems' disruption, such as resistance to microbial colonization. This study highlights the role of weak transcriptional activity taxa in maintaining a stable honeybee gut microbiota. Finally, the early detection of gut dysbiosis in honeybees is a promising biomarker in hive management for assessing the impact exposure to sublethal xenobiotics.

An Organ System-Based Synopsis of Pseudomonas aeruginosa Virulence.

Driven in part by its metabolic versatility, high intrinsic antibiotic resistance, and a large repertoire of virulence factors, Pseudomonas aeruginosa is expertly adapted to thrive in a wide variety of environments, and in the process, making it a notorious opportunistic pathogen. Apart from the extensively studied chronic infection in the lungs of people with cystic fibrosis (CF), P. aeruginosa also causes multiple serious infections encompassing essentially all organs of the human body, among others, lung infection in patients with chronic obstructive pulmonary disease, primary ciliary dyskinesia and ventilator-associated pneumonia; bacteremia and sepsis; soft tissue infection in burns, open wounds and postsurgery patients; urinary tract infection; diabetic foot ulcers; chronic suppurative otitis media and otitis externa; and keratitis associated with extended contact lens use. Although well characterized in the context of CF, pathogenic processes mediated by various P. aeruginosa virulence factors in other organ systems remain poorly understood. In this review, we use an organ system-based approach to provide a synopsis of disease mechanisms exerted by P. aeruginosa virulence determinants that contribute to its success as a versatile pathogen.

Evenness-Richness Scatter Plots: a Visual and Insightful Representation of Shannon Entropy Measurements for Ecological Community Analysis.

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. By decoupling both components measured by Shannon's entropy, two communities having identical indices can be differentiated by mapping richness and evenness coordinates on a scatter plot. In such graphs, confidence ellipses would allow testing significant differences between groups of samples. Multivariate statistical tests such as permutational multivariate analysis of variance (PERMANOVA) can be performed on distance matrices calculated from richness and evenness coordinates and detect statistically significant differences that would have remained unforeseen otherwise. Therefore, plotting richness and evenness on two-dimensional (2D) graphs gives a more thorough understanding of how alpha diversity differs between groups of samples.

Neural anatomy and optical microscopy (NAOMi) simulation for evaluating calcium imaging methods.

BACKGROUND: The past decade has seen a multitude of new in vivo functional imaging methodologies. However, the lack of ground-truth comparisons or evaluation metrics makes the large-scale, systematic validation vital to the continued development and use of optical microscopy impossible. NEW-METHOD: We provide a new framework for evaluating two-photon microscopy methods via in silico Neural Anatomy and Optical Microscopy (NAOMi) simulation. Our computationally efficient model generates large anatomical volumes of mouse cortex, simulates neural activity, and incorporates optical propagation and scanning to create realistic calcium imaging datasets. RESULTS: We verify NAOMi simulations against in vivo two-photon recordings from mouse cortex. We leverage this in silico ground truth to directly compare different segmentation algorithms and optical designs. We find modern segmentation algorithms extract strong neural time-courses comparable to estimation using oracle spatial information, but with an increase in the false positive rate. Comparison between optical setups demonstrate improved resilience to motion artifacts in sparsely labeled samples using Bessel beams, increased signal-to-noise ratio and cell-count using low numerical aperture Gaussian beams and nuclear GCaMP, and more uniform spatial sampling with temporal focusing versus multi-plane imaging. COMPARISON WITH EXISTING METHODS: NAOMi is a first-of-its kind framework for assessing optical imaging modalities. Existing methods are either anatomical simulations or do not address functional imaging. Thus there is no competing method for simulating realistic functional optical microscopy data. CONCLUSIONS: By leveraging the rich accumulated knowledge of neural anatomy and optical physics, we provide a powerful new tool to assess and develop important methods in neural imaging.

Complete Genome Sequence of a Pseudomonas Species Isolated from Tailings Pond Water in Alberta, Canada.

We report the complete genome sequence of strain OST1909, belonging to a Pseudomonas species. The genome size is 6,306,352 bp, with a G+C content of 59.6%. The isolate was recovered from oil sands process-affected water (OSPW), despite the numerous toxic compounds that accumulate in oil sands tailings ponds.