Estimation of country-specific tuberculosis resistance antibiograms using pathogen genomics and machine learning

BACKGROUND

Global tuberculosis (TB) drug resistance (DR) surveillance focuses on rifampicin. We examined the potential of public and surveillance Mycobacterium tuberculosis (Mtb) whole-genome sequencing (WGS) data, to generate expanded country-level resistance prevalence estimates (antibiograms) using in silico resistance prediction.

METHODS

We curated and quality-controlled Mtb WGS data. We used a validated random forest model to predict phenotypic resistance to 12 drugs and bias-corrected for model performance, outbreak sampling and rifampicin resistance oversampling. Validation leveraged a national DR survey conducted in South Africa.

RESULTS

Mtb isolates from 29 countries (n=19 149) met sequence quality criteria. Global marginal genotypic resistance among mono-resistant TB estimates overlapped with the South African DR survey, except for isoniazid, ethionamide and second-line injectables, which were underestimated (n=3134). Among multidrug resistant (MDR) TB (n=268), estimates overlapped for the fluoroquinolones but overestimated other drugs. Globally pooled mono-resistance to isoniazid was 10.9% (95% CI: 10.2-11.7%, n=14 012). Mono-levofloxacin resistance rates were highest in South Asia (Pakistan 3.4% (0.1-11%), n=111 and India 2.8% (0.08-9.4%), n=114). Given the recent interest in drugs enhancing ethionamide activity and their expected activity against isolates with resistance discordance between isoniazid and ethionamide, we measured this rate and found it to be high at 74.4% (IQR: 64.5-79.7%) of isoniazid-resistant isolates predicted to be ethionamide susceptible. The global susceptibility rate to pyrazinamide and levofloxacin among MDR was 15.1% (95% CI: 10.2-19.9%, n=3964).

CONCLUSIONS

This is the first attempt at global Mtb antibiogram estimation. DR prevalence in Mtb can be reliably estimated using public WGS and phenotypic resistance prediction for key antibiotics, but public WGS data demonstrates oversampling of isolates with higher resistance levels than MDR. Nevertheless, our results raise concerns about the empiric use of short-course fluoroquinolone regimens for drug-susceptible TB in South Asia and indicate underutilisation of ethionamide in MDR treatment.

Phase variation as a major mechanism of adaptation in Mycobacterium tuberculosis complex

Phase variation induced by insertions and deletions (INDELs) in genomic homopolymeric tracts (HT) can silence and regulate genes in pathogenic bacteria, but this process is not characterized in MTBC (Mycobacterium tuberculosis complex) adaptation. We leverage 31,428 diverse clinical isolates to identify genomic regions including phase-variants under positive selection. Of 87,651 INDEL events that emerge repeatedly across the phylogeny, 12.4% are phase-variants within HTs (0.02% of the genome by length). We estimated the in-vitro frameshift rate in a neutral HT at 100× the neutral substitution rate at [Formula: see text] frameshifts/HT/year. Using neutral evolution simulations, we identified 4,098 substitutions and 45 phase-variants to be putatively adaptive to MTBC (P < 0.002). We experimentally confirm that a putatively adaptive phase-variant alters the expression of espA, a critical mediator of ESX-1-dependent virulence. Our evidence supports the hypothesis that phase variation in the ESX-1 system of MTBC can act as a toggle between antigenicity and survival in the host.

Analysis of genome-wide mutational dependence in naturally evolving Mycobacterium tuberculosis populations

Pathogenic micro-organisms are in a perpetual struggle for survival in changing host environments, where host pressures necessitate changes in pathogen virulence, antibiotic resistance, or transmissibility. The genetic basis of phenotypic adaptation by pathogens is difficult to study in vivo. In this work, we develop a phylogenetic method to detect genetic dependencies that promote pathogen adaptation using 31,428 in vivo sampled Mycobacterium tuberculosis genomes, a globally prevalent bacterial pathogen with increasing levels of antibiotic resistance. We find that dependencies between mutations are enriched in antigenic and antibiotic resistance functions, and discover 23 mutations that potentiate the development of antibiotic resistance. Between 11% and 92% of resistant strains harbor a dependent mutation acquired after a resistance-conferring variant. We demonstrate the pervasiveness of genetic dependency in adaptation of naturally evolving populations and the utility of the proposed computational approach. Data and code available at: https://github.com/farhat-lab/DependentMutations.

A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis

Long diagnostic wait times hinder international efforts to address antibiotic resistance in M. tuberculosis. Pathogen whole genome sequencing, coupled with statistical and machine learning models, offers a promising solution. However, generalizability and clinical adoption have been limited by a lack of interpretability, especially in deep learning methods. Here, we present two deep convolutional neural networks that predict antibiotic resistance phenotypes of M. tuberculosis isolates: a multi-drug CNN (MD-CNN), that predicts resistance to 13 antibiotics based on 18 genomic loci, with AUCs 82.6-99.5% and higher sensitivity than state-of-the-art methods; and a set of 13 single-drug CNNs (SD-CNN) with AUCs 80.1-97.1% and higher specificity than the previous state-of-the-art. Using saliency methods to evaluate the contribution of input sequence features to the SD-CNN predictions, we identify 18 sites in the genome not previously associated with resistance. The CNN models permit functional variant discovery, biologically meaningful interpretation, and clinical applicability.

1397. Modern Lineages of Mycobacterium tuberculosis Were Recently Introduced in Western India and Demonstrate Increased Transmissibility

Background

Mycobacterium tuberculosis (Mtb) transmissibility may vary between lineages (or variants) and this may contribute to the slow decline of tuberculosis incidence. The objective of our study was to compare transmissibility across four major lineages (L1-4) of Mtb in Pune, India.

Methods

We performed whole-genome sequencing (WGS) of Mtb isolated from sputum culture of adult patients with pulmonary TB. We performed genotypic susceptibility testing for both first- and second-line drugs using a previously validated random forest predictor. We identified single nucleotide polymorphisms and generated a multiple sequence alignment excluding drug resistance conferring mutations to avoid skewing the phylogeny due to convergent evolution in these regions. We used Bayesian molecular dating to generate phylogenies and compared tree characteristics using a two-sample Kolmogorov-Smirnov (KS) test.

Results

Of the 642 isolates from distinct study participants that underwent WGS, 612 met quality criteria. The median age of participants was 31 years (range 18-74), the majority were male (64.7%) and sputum smear-positive (83.3%), and 6.7% had co-infection with HIV (Table 1). There was no significant difference in baseline characteristics between lineages. The majority of isolates belonged to L3 (44.6%). The majority (61.1%) of multidrug-resistant (MDR, resistant to isoniazid and rifampin) isolates belonged to L2. In phylogenetic analysis, we found evidence of higher transmissibility of L2 as indicated by shorter branch lengths (i.e., less time had elapsed between transmission and sampling) and more genetic similarity (smaller pairwise single nucleotide polymorphism [SNP] distances) among L2 isolates as compared to other lineages (Figure 1). Branching times for L2 and L4 were smaller than L1 and L3 indicating recent introduction into the region (p < 0.001 [KS test]).

Figure 1: Lineage-wise distribution of A) phylogenetic tree branch lengths (log) and B) pairwise single nucleotide polymorphism (SNP) distance, using 612 tuberculosis isolates from Pune, India. P values calculated using two-sample Kolmogorov-Smirnov test.

Table 1: Demographic characteristics of study participants included in the study, by lineage.

Conclusion

Modern Mtb lineages (L2 and L4) were relatively recently introduced in western India, as compared to older lineages (L1 and L3), with the more drug-resistant L2 showing higher transmissibility. These findings highlight the need for early detection and treatment initiation to interrupt transmission with important implications for antimicrobial stewardship and heightened surveillance of TB resistance rates.

Disclosures

All Authors: No reported disclosures

Population structure, biogeography and transmissibility of Mycobacterium tuberculosis

Mycobacterium tuberculosis is a clonal pathogen proposed to have co-evolved with its human host for millennia, yet our understanding of its genomic diversity and biogeography remains incomplete. Here we use a combination of phylogenetics and dimensionality reduction to reevaluate the population structure of M. tuberculosis, providing an in-depth analysis of the ancient Indo-Oceanic Lineage 1 and the modern Central Asian Lineage 3, and expanding our understanding of Lineages 2 and 4. We assess sub-lineages using genomic sequences from 4939 pan-susceptible strains, and find 30 new genetically distinct clades that we validate in a dataset of 4645 independent isolates. We find a consistent geographically restricted or unrestricted pattern for 20 groups, including three groups of Lineage 1. The distribution of terminal branch lengths across the M. tuberculosis phylogeny supports the hypothesis of a higher transmissibility of Lineages 2 and 4, in comparison with Lineages 3 and 1, on a global scale. We define an expanded barcode of 95 single nucleotide substitutions that allows rapid identification of 69 M. tuberculosis sub-lineages and 26 additional internal groups. Our results paint a higher resolution picture of the M. tuberculosis phylogeny and biogeography.

Role of Epistasis in Amikacin, Kanamycin, Bedaquiline, and Clofazimine Resistance in Mycobacterium tuberculosis Complex

Antibiotic resistance among bacterial pathogens poses a major global health threat. Mycobacterium tuberculosis complex (MTBC) is estimated to have the highest resistance rates of any pathogen globally. Given the low growth rate and the need for a biosafety level 3 laboratory, the only realistic avenue to scale up drug susceptibility testing (DST) for this pathogen is to rely on genotypic techniques. This raises the fundamental question of whether a mutation is a reliable surrogate for phenotypic resistance or whether the presence of a second mutation can completely counteract its effect, resulting in major diagnostic errors (i.e., systematic false resistance results). To date, such epistatic interactions have only been reported for streptomycin that is now rarely used. By analyzing more than 31,000 MTBC genomes, we demonstrated that the eis C-14T promoter mutation, which is interrogated by several genotypic DST assays endorsed by the World Health Organization, cannot confer resistance to amikacin and kanamycin if it coincides with loss-of-function (LoF) mutations in the coding region of eis. To our knowledge, this represents the first definitive example of antibiotic reversion in MTBC. Moreover, we raise the possibility that mmpR (Rv0678) mutations are not valid markers of resistance to bedaquiline and clofazimine if these coincide with an LoF mutation in the efflux pump encoded by mmpS5 (Rv0677c) and mmpL5 (Rv0676c).

GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning

BACKGROUND

Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly and accurate resistance prediction tools are needed to enable public health and clinical practitioners to rapidly diagnose resistance and inform treatment regimens.

RESULTS

We present Translational Genomics platform for Tuberculosis (GenTB), a free and open web-based application to predict antibiotic resistance from next-generation sequence data. The user can choose between two potential predictors, a Random Forest (RF) classifier and a Wide and Deep Neural Network (WDNN) to predict phenotypic resistance to 13 and 10 anti-tuberculosis drugs, respectively. We benchmark GenTB's predictive performance along with leading TB resistance prediction tools (Mykrobe and TB-Profiler) using a ground truth dataset of 20,408 isolates with laboratory-based drug susceptibility data. All four tools reliably predicted resistance to first-line tuberculosis drugs but had varying performance for second-line drugs. The mean sensitivities for GenTB-RF and GenTB-WDNN across the nine shared drugs were 77.6% (95% CI 76.6-78.5%) and 75.4% (95% CI 74.5-76.4%), respectively, and marginally higher than the sensitivities of TB-Profiler at 74.4% (95% CI 73.4-75.3%) and Mykrobe at 71.9% (95% CI 70.9-72.9%). The higher sensitivities were at an expense of ≤ 1.5% lower specificity: Mykrobe 97.6% (95% CI 97.5-97.7%), TB-Profiler 96.9% (95% CI 96.7 to 97.0%), GenTB-WDNN 96.2% (95% CI 96.0 to 96.4%), and GenTB-RF 96.1% (95% CI 96.0 to 96.3%). Averaged across the four tools, genotypic resistance sensitivity was 11% and 9% lower for isoniazid and rifampicin respectively, on isolates sequenced at low depth (< 10× across 95% of the genome) emphasizing the need to quality control input sequence data before prediction. We discuss differences between tools in reporting results to the user including variants underlying the resistance calls and any novel or indeterminate variants CONCLUSIONS: GenTB is an easy-to-use online tool to rapidly and accurately predict resistance to anti-tuberculosis drugs. GenTB can be accessed online at https://gentb.hms.harvard.edu , and the source code is available at https://github.com/farhat-lab/gentb-site .

Transmission, adaptation and geographical spread of the Pseudomonas aeruginosa Liverpool epidemic strain

The Liverpool epidemic strain (LES) is an important transmissible clonal lineage of Pseudomonas aeruginosa that chronically infects the lungs of people with cystic fibrosis (CF). Previous studies have focused on the genomics of the LES in a limited number of isolates, mostly from one CF centre in the UK, and from studies highlighting identification of the LES in Canada. Here we significantly extend the current LES genome database by genome sequencing 91 isolates from multiple CF centres across the UK, and we describe the comparative genomics of this large collection of LES isolates from the UK and Canada. Phylogenetic analysis revealed that the 145 LES genomes analysed formed a distinct clonal lineage when compared with the wider P. aeruginosa population. Notably, the isolates formed two clades: one associated with isolates from Canada, and the other associated with UK isolates. Further analysis of the UK LES isolates revealed clustering by clinic geography. Where isolates clustered closely together, the association was often supported by clinical data linking isolates or patients. When compared with the earliest known isolate, LESB58 (from 1988), many UK LES isolates shared common loss-of-function mutations, such as in genes gltR and fleR. Other loss-of-function mutations identified in previous studies as common adaptations during CF chronic lung infections were also identified in multiple LES isolates. Analysis of the LES accessory genome (including genomic islands and prophages) revealed variations in the carriage of large genomic regions, with some evidence for shared genomic island/prophage complement according to clinic location. Our study reveals divergence and adaptation during the spread of the LES, within the UK and between continents.

In-host population dynamics of Mycobacterium tuberculosis complex during active disease

Tuberculosis (TB) is a leading cause of death globally. Understanding the population dynamics of TB’s causative agent Mycobacterium tuberculosis complex (Mtbc) in-host is vital for understanding the efficacy of antibiotic treatment. We use longitudinally collected clinical Mtbc isolates that underwent Whole-Genome Sequencing from the sputa of 200 patients to investigate Mtbc diversity during the course of active TB disease after excluding 107 cases suspected of reinfection, mixed infection or contamination. Of the 178/200 patients with persistent clonal infection >2 months, 27 developed new resistance mutations between sampling with 20/27 occurring in patients with pre-existing resistance. Low abundance resistance variants at a purity of ≥19% in the first isolate predict fixation in the subsequent sample. We identify significant in-host variation in 27 genes, including antibiotic resistance genes, metabolic genes and genes known to modulate host innate immunity and confirm several to be under positive selection by assessing phylogenetic convergence across a genetically diverse sample of 20,352 isolates.

Globally diverse Mycobacterium tuberculosis resistance acquisition: a retrospective geographical and temporal analysis of whole genome sequences

Background

Mycobacterium tuberculosis whole genome sequencing (WGS) data can provide insights into temporal and geographical trends in resistance acquisition and inform public health interventions. We aimed to use a large clinical collection of M tuberculosis WGS and resistance phenotype data to study how, when, and where resistance was acquired on a global scale.

Methods

We did a retrospective analysis of WGS data. We curated a set of clinical M tuberculosis isolates with high-quality sequencing and culture-based drug susceptibility data (spanning four lineages and 52 countries in Africa, Asia, the Americas, and Europe) using public databases and literature curation. For inclusion, sequence quality criteria and country of origin data were required. We constructed geographical and lineage specific M tuberculosis phylogenies and used Bayesian molecular dating with BEAST, version 1.10.4, to infer the most recent common susceptible ancestor age for 4869 instances of resistance to ten drugs.

Findings

Between Jan 1, 1987, and Sept 12, 2014, of 10 299 M tuberculosis clinical isolates, 8550 were curated, of which 6099 (71%) from 15 countries met criteria for molecular dating. The number of independent resistance acquisition events was lower than the number of resistant isolates across all countries, suggesting ongoing transmission of drug resistance. Ancestral age distributions supported the presence of old resistance, 20 years or more before, in most countries. A consistent order of resistance acquisition was observed globally starting with resistance to isoniazid, but resistance ancestral age varied by country. We found a direct correlation between gross domestic product per capita and resistance age (r ²=0·47; p=0·014). Amplification of fluoroquinolone and second-line injectable resistance among multidrug-resistant isolates is estimated to have occurred very recently (median ancestral age 4·7 years [IQR 1·9-9·8] before sample collection). We found the sensitivity of commercial molecular diagnostics for second-line resistance to vary significantly by country (p<0·0003).

Interpretation

Our results highlight that both resistance transmission and amplification are contributing to disease burden globally but vary by country. The observation that wealthier nations are more likely to have old resistance (most recent common susceptible ancestor >20 years before isolation) suggests that programmatic improvements can reduce resistance amplification, but that fit resistant strains can circulate for decades subsequently implies the need for continued surveillance.

1653. Estimation of country-specific tuberculosis antibiograms using a wide and deep neural net on a large genomic dataset

Background

Improved estimates of drug resistant tuberculosis (TB) burden are needed to aid control efforts. The World Health Organization (WHO) currently reports estimates for rifampin resistance (RR) or multidrug resistance (MDR) at the national level. Resistance rates to other first-line and second-line agents, e.g. ethambutol, pyrazinamide, and aminoglycosides, are rarely available, even at the country level. Our objective was to generate country and drug specific resistance prevalence estimates (antibiograms) using in silico phenotype prediction and curated public and surveillance Mycobacterium tuberculosis (MTB) genomic data.

Methods

We curated MTB genomes either by sequencing or from published literature and excluded genomes that did not meet our quality criteria (i.e. at least 10X depth in >95% of the genome). A machine learning model previously trained to predict phenotypic resistance in MTB with high accuracy, a wide and deep neural net (WDNN), was used to predict resistance to ten drugs. We corrected for resistance oversampling in genomic data by conditioning on RR and using country specific surveillance MDR/RR rates reported by the WHO.

Results

Of the 49,851 MTB genomes curated, 33,873 isolates met quality criteria. Of these, geographic data was available for 22,838 genomes. Antibiograms were generated for nine first- and second-line drugs for 36 countries. Among countries with at least 100 isolates, a high rate of resistance to fluoroquinolones and second line injectables was seen among isolates from the Republic of Moldova (15.4% [CI = 13.7-16.7%] moxifloxacin resistant, 6.3% [CI = 5.5-6.8%] kanamycin resistant, n = 330) and Russian Federation (9.3% [CI = 9.1-9.4] moxifloxacin resistant, 5.4% [CI = 5.3-5.5%] kanamycin resistant, n = 1011) (Figure 1).

Figure 1: Antibiograms created using genotypic data for isolates from Republic of Moldova (n=330, rifampin-resistance rate correction: 29%, range 26-31% among new tuberculosis cases);and Russian Federation (n=1011, rifampin-resistance rate correction 35%, range 34-35%, among new tuberculosis cases. rif: rifampin, inh: isoniazid, pza: pyrazinamide, emb: ethambutol, str: streptomycin, cap: capreomycin, amk: amikacin, kan: kanamycin, moxi: moxifloxacin

Conclusion

The estimation of antibiotic resistance prevalence in MTB for pyrazinamide, ethambutol and second-line agents can be aided by the use of in silico models of drug resistance. A high rate of resistance to second-line drugs precludes large scale roll out of short-course WHO regimens for treatment of MDR-TB for empiric use in certain countries. The use of whole genome sequencing for resistance surveillance can inform policy on optimal national regimen choice for TB treatment.

Disclosures

All Authors: No reported disclosures

Genomic characterisation of an international Pseudomonas aeruginosa reference panel indicates that the two major groups draw upon distinct mobile gene pools

Pseudomonas aeruginosa is an important opportunistic pathogen, especially in the context of infections of cystic fibrosis (CF). In order to facilitate coordinated study of this pathogen, an international reference panel of P. aeruginosa isolates was assembled. Here we report the genome sequencing and analysis of 33 of these isolates and 7 reference genomes to further characterise this panel. Core genome single nucleotide variant phylogeny demonstrated that the panel strains are widely distributed amongst the P. aeruginosa population. Common loss-of-function mutations reported as adaptive during CF (such as in mucA and mexA) were identified amongst isolates from chronic respiratory infections. From the 40 strains analysed, 37 unique resistomes were predicted, based on the Resistance Gene Identifier method using the Comprehensive Antibiotic Resistance Database. Notably, hierarchical clustering and phylogenetic reconstructions based on the presence/absence of genomic islands (GIs), prophages and other regions of genome plasticity (RGPs) supported the subdivision of P. aeruginosa into two main groups. This is the largest, most diverse analysis of GIs and associated RGPs to date, and the results suggest that, at least at the largest clade grouping level (group 1 vs group 2), each group may be drawing upon distinct mobile gene pools.

Reservoirs of resistance: polymyxin resistance in veterinary-associated companion animal isolates of Pseudomonas aeruginosa

BACKGROUND

Pseudomonas aeruginosa is an opportunistic pathogen and a major cause of infections. Widespread resistance in human infections are increasing the use of last resort antimicrobials such as polymyxins. However, these have been used for decades in veterinary medicine. Companion animals are an understudied source of antimicrobial resistant P. aeruginosa isolates. This study evaluated the susceptibility of P. aeruginosa veterinary isolates to polymyxins to determine whether the veterinary niche represents a potential reservoir of resistance genes for pathogenic bacteria in both animals and humans.

METHODS AND RESULTS

Clinical P. aeruginosa isolates (n=24) from UK companion animals were compared for antimicrobial susceptibility to a panel of human-associated isolates (n=37). Minimum inhibitory concentration (MIC) values for polymyxin B and colistin in the companion animals was significantly higher than in human isolates (P=0.033 and P=0.013, respectively). Genotyping revealed that the veterinary isolates were spread throughout the P. aeruginosa population, with shared array types from human infections such as keratitis and respiratory infections, suggesting the potential for zoonotic transmission. Whole genome sequencing revealed mutations in genes associated with polymyxin resistance and other antimicrobial resistance-related genes.

CONCLUSION

The high levels of resistance to polymyxin shown here, along with genetic similarities between some human and animal isolates, together suggest a need for sustained surveillance of this veterinary niche as a potential reservoir for resistant, clinically relevant bacteria in both animals and humans.

Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction

Background

Methods

Findings

Interpretation

Whole genome sequencing identifies bacterial factors affecting transmission of multidrug-resistant tuberculosis in a high-prevalence setting

Whole genome sequencing (WGS) can elucidate Mycobacterium tuberculosis (Mtb) transmission patterns but more data is needed to guide its use in high-burden settings. In a household-based TB transmissibility study in Peru, we identified a large MIRU-VNTR Mtb cluster (148 isolates) with a range of resistance phenotypes, and studied host and bacterial factors contributing to its spread. WGS was performed on 61 of the 148 isolates. We compared transmission link inference using epidemiological or genomic data and estimated the dates of emergence of the cluster and antimicrobial drug resistance (DR) acquisition events by generating a time-calibrated phylogeny. Using a set of 12,032 public Mtb genomes, we determined bacterial factors characterizing this cluster and under positive selection in other Mtb lineages. Four of the 61 isolates were distantly related and the remaining 57 isolates diverged ca. 1968 (95%HPD: 1945-1985). Isoniazid resistance arose once and rifampin resistance emerged subsequently at least three times. Emergence of other DR types occurred as recently as within the last year of sampling. We identified five cluster-defining SNPs potentially contributing to transmissibility. In conclusion, clusters (as defined by MIRU-VNTR typing) may be circulating for decades in a high-burden setting. WGS allows for an enhanced understanding of transmission, drug resistance, and bacterial fitness factors.

The Pseudomonas aeruginosa Pan-Genome Provides New Insights on Its Population Structure, Horizontal Gene Transfer, and Pathogenicity

The huge increase in the availability of bacterial genomes led us to a point in which we can investigate and query pan-genomes, for example, the full set of genes of a given bacterial species or clade. Here, we used a data set of 1,311 high-quality genomes from the human pathogen Pseudomonas aeruginosa, 619 of which were newly sequenced, to show that a pan-genomic approach can greatly refine the population structure of bacterial species, provide new insights to define species boundaries, and generate hypotheses on the evolution of pathogenicity. The 665-gene P. aeruginosa core genome presented here, which constitutes only 1% of the entire pan-genome, is the first to be in the same order of magnitude as the minimal bacterial genome and represents a conservative estimate of the actual core genome. Moreover, the phylogeny based on this core genome provides strong evidence for a five-group population structure that includes two previously undescribed groups of isolates. Comparative genomics focusing on antimicrobial resistance and virulence genes showed that variation among isolates was partly linked to this population structure. Finally, we hypothesized that horizontal gene transfer had an important role in this respect, and found a total of 3,010 putative complete and fragmented plasmids, 5% and 12% of which contained resistance or virulence genes, respectively. This work provides data and strategies to study the evolutionary trajectories of resistance and virulence in P. aeruginosa.

Salmonella enterica Prophage Sequence Profiles Reflect Genome Diversity and Can Be Used for High Discrimination Subtyping

Non-typhoidal Salmonella is a leading cause of foodborne illness worldwide. Prompt and accurate identification of the sources of Salmonella responsible for disease outbreaks is crucial to minimize infections and eliminate ongoing sources of contamination. Current subtyping tools including single nucleotide polymorphism (SNP) typing may be inadequate, in some instances, to provide the required discrimination among epidemiologically unrelated Salmonella strains. Prophage genes represent the majority of the accessory genes in bacteria genomes and have potential to be used as high discrimination markers in Salmonella. In this study, the prophage sequence diversity in different Salmonella serovars and genetically related strains was investigated. Using whole genome sequences of 1,760 isolates of S. enterica representing 151 Salmonella serovars and 66 closely related bacteria, prophage sequences were identified from assembled contigs using PHASTER. We detected 154 different prophages in S. enterica genomes. Prophage sequences were highly variable among S. enterica serovars with a median ± interquartile range (IQR) of 5 ± 3 prophage regions per genome. While some prophage sequences were highly conserved among the strains of specific serovars, few regions were lineage specific. Therefore, strains belonging to each serovar could be clustered separately based on their prophage content. Analysis of S. Enteritidis isolates from seven outbreaks generated distinct prophage profiles for each outbreak. Taken altogether, the diversity of the prophage sequences correlates with genome diversity. Prophage repertoires provide an additional marker for differentiating S. enterica subtypes during foodborne outbreaks.

Comparative genomics of a drug-resistant Pseudomonas aeruginosa panel and the challenges of antimicrobial resistance prediction from genomes

Antimicrobial resistance (AMR) is now recognized as a global threat to human health. The accessibility of microbial whole-genome sequencing offers an invaluable opportunity for resistance surveillance via the resistome, i.e. the genes and mutations underlying AMR. Unfortunately, AMR prediction from genomic data remains extremely challenging, especially for species with a large pan-genome. One such organism, for which multidrug-resistant (MDR) isolates are frequently encountered in the clinic, is Pseudomonas aeruginosa. This study focuses on a commercially available panel of seven MDR P. aeruginosa strains. The main goals were to sequence and compare these strains' genomes, attempt to predict AMR from whole genomes using two different methods and determine whether this panel could be an informative complement to the international P. aeruginosa reference panel. As expected, the results highlight the complexity of associating genotype and AMR phenotype in P. aeruginosa, mainly due to the intricate regulation of resistance mechanisms. Our results also urge caution in the interpretation of predicted resistomes regarding the occurrence of gene identity discrepancies between strains. We envision that, in addition to accounting for the genomic diversity of P. aeruginosa, future development of predictive tools will need to incorporate a transcriptomic, proteomic and/or metabolomic component.

Genomic characterisation of environmental Pseudomonas aeruginosa isolated from dental unit waterlines revealed the insertion sequence ISPa11 as a chaotropic element

The bacterium Pseudomonas aeruginosa is well known to have a remarkable adaptive capacity allowing it to colonise many environments. A recent study on environmental isolates from dental unit waterlines (DUWLs) hinted at a genetic clustering into two groups. Isolates from one of these groups, named cluster III, were shown to have unusual phenotypes for environmental isolates, such as an increased biofilm production. To have a better ecological view, more specifically on isolates from cluster III, the complete genomes of 39 isolates including 16 from DUWLs were sequenced. In addition to an investigation of antibiotic resistance and secretion system gene content, a molecular phylogeny allowed confirmation of the split of the 16 environmental isolates in two groups and also sheds light on a correlation between the phylogenetic positions and the serotypes of the isolates. Isolates from cluster III harboured insertion sequences ISPa11 inserted into the O-specific antigen biosynthesis clusters and the gene lasR, encoding for a master regulator of the quorum sensing. Investigation of key regulators revealed another truncated gene, gacS. Alteration in lasR and gacS genes was consistent with phenotypic assays confirming their inactivation. These results bring new perspectives regarding the ecological adaptive potential of P. aeruginosa.

Comparative analysis of mitochondrial genomes of geographic variants of the gypsy moth, Lymantria dispar, reveals a previously undescribed genotypic entity

The gypsy moth, Lymantria dispar L., is one of the most destructive forest pests in the world. While the subspecies established in North America is the European gypsy moth (L. dispar dispar), whose females are flightless, the two Asian subspecies, L. dispar asiatica and L. dispar japonica, have flight-capable females, enhancing their invasiveness and warranting precautionary measures to prevent their permanent establishment in North America. Various molecular tools have been developed to help distinguish European from Asian subspecies, several of which are based on the mitochondrial barcode region. In an effort to identify additional informative markers, we undertook the sequencing and analysis of the mitogenomes of 10 geographic variants of L. dispar, including two or more variants of each subspecies, plus the closely related L. umbrosa as outgroup. Several regions of the gypsy moth mitogenomes displayed nucleotide substitutions with potential usefulness for the identification of subspecies and/or geographic origins. Interestingly, the mitogenome of one geographic variant displayed significant divergence relative to the remaining variants, raising questions about its taxonomic status. Phylogenetic analyses placed this population from northern Iran as basal to the L. dispar clades. The present findings will help improve diagnostic tests aimed at limiting risks of AGM invasions.

Prophage Integrase Typing Is a Useful Indicator of Genomic Diversity in Salmonella enterica

Salmonella enterica is a bacterial species that is a major cause of illness in humans and food-producing animals. S. enterica exhibits considerable inter-serovar diversity, as evidenced by the large number of host adapted serovars that have been identified. The development of methods to assess genome diversity in S. enterica will help to further define the limits of diversity in this foodborne pathogen. Thus, we evaluated a PCR assay, which targets prophage integrase genes, as a rapid method to investigate S. enterica genome diversity. To evaluate the PCR prophage integrase assay, 49 isolates of S. enterica were selected, including 19 clinical isolates from clonal serovars (Enteritidis and Heidelberg) that commonly cause human illness, and 30 isolates from food-associated Salmonella serovars that rarely cause human illness. The number of integrase genes identified by the PCR assay was compared to the number of integrase genes within intact prophages identified by whole genome sequencing and phage finding program PHASTER. The PCR assay identified a total of 147 prophage integrase genes within the 49 S. enterica genomes (79 integrase genes in the food-associated Salmonella isolates, 50 integrase genes in S. Enteritidis, and 18 integrase genes in S. Heidelberg). In comparison, whole genome sequencing and PHASTER identified a total of 75 prophage integrase genes within 102 intact prophages in the 49 S. enterica genomes (44 integrase genes in the food-associated Salmonella isolates, 21 integrase genes in S. Enteritidis, and 9 integrase genes in S. Heidelberg). Collectively, both the PCR assay and PHASTER identified the presence of a large diversity of prophage integrase genes in the food-associated isolates compared to the clinical isolates, thus indicating a high degree of diversity in the food-associated isolates, and confirming the clonal nature of S. Enteritidis and S. Heidelberg. Moreover, PHASTER revealed a diversity of 29 different types of prophages and 23 different integrase genes within the food-associated isolates, but only identified four different phages and integrase genes within clonal isolates of S. Enteritidis and S. Heidelberg. These results demonstrate the potential usefulness of PCR based detection of prophage integrase genes as a rapid indicator of genome diversity in S. enterica.

Genomics of antibiotic-resistance prediction in Pseudomonas aeruginosa

Antibiotic resistance is a worldwide health issue spreading quickly among human and animal pathogens, as well as environmental bacteria. Misuse of antibiotics has an impact on the selection of resistant bacteria, thus contributing to an increase in the occurrence of resistant genotypes that emerge via spontaneous mutation or are acquired by horizontal gene transfer. There is a specific and urgent need not only to detect antimicrobial resistance but also to predict antibiotic resistance in silico. We now have the capability to sequence hundreds of bacterial genomes per week, including assembly and annotation. Novel and forthcoming bioinformatics tools can predict the resistome and the mobilome with a level of sophistication not previously possible. Coupled with bacterial strain collections and databases containing strain metadata, prediction of antibiotic resistance and the potential for virulence are moving rapidly toward a novel approach in molecular epidemiology. Here, we present a model system in antibiotic-resistance prediction, along with its promises and limitations. As it is commonly multidrug resistant, Pseudomonas aeruginosa causes infections that are often difficult to eradicate. We review novel approaches for genotype prediction of antibiotic resistance. We discuss the generation of microbial sequence data for real-time patient management and the prediction of antimicrobial resistance.

A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis

The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.

A Pan-Genomic Approach to Understand the Basis of Host Adaptation in Achromobacter

Over the past decade, there has been a rising interest in Achromobacter sp., an emerging opportunistic pathogen responsible for nosocomial and cystic fibrosis lung infections. Species of this genus are ubiquitous in the environment, can outcompete resident microbiota, and are resistant to commonly used disinfectants as well as antibiotics. Nevertheless, the Achromobacter genus suffers from difficulties in diagnosis, unresolved taxonomy and limited understanding of how it adapts to the cystic fibrosis lung, not to mention other host environments. The goals of this first genus-wide comparative genomics study were to clarify the taxonomy of this genus and identify genomic features associated with pathogenicity and host adaptation. This was done with a widely applicable approach based on pan-genome analysis. First, using all publicly available genomes, a combination of phylogenetic analysis based on 1,780 conserved genes with average nucleotide identity and accessory genome composition allowed the identification of a largely clinical lineage composed of Achromobacter xylosoxidans, Achromobacter insuavis, Achromobacter dolens, and Achromobacter ruhlandii. Within this lineage, we identified 35 positively selected genes involved in metabolism, regulation and efflux-mediated antibiotic resistance. Second, resistome analysis showed that this clinical lineage carried additional antibiotic resistance genes compared with other isolates. Finally, we identified putative mobile elements that contribute 53% of the genus's resistome and support horizontal gene transfer between Achromobacter and other ecologically similar genera. This study provides strong phylogenetic and pan-genomic bases to motivate further research on Achromobacter, and contributes to the understanding of opportunistic pathogen evolution.

A Multi-Species TaqMan PCR Assay for the Identification of Asian Gypsy Moths (Lymantria spp.) and Other Invasive Lymantriines of Biosecurity Concern to North America

Preventing the introduction and establishment of forest invasive alien species (FIAS) such as the Asian gypsy moth (AGM) is a high-priority goal for countries with extensive forest resources such as Canada. The name AGM designates a group of closely related Lymantria species (Lepidoptera: Erebidae: Lymantriinae) comprising two L. dispar subspecies (L. dispar asiatica, L. dispar japonica) and three closely related Lymantria species (L. umbrosa, L. albescens, L. postalba), all considered potential FIAS in North America. Ships entering Canadian ports are inspected for the presence of suspicious gypsy moth eggs, but those of AGM are impossible to distinguish from eggs of innocuous Lymantria species. To assist regulatory agencies in their identification of these insects, we designed a suite of TaqMan^® assays that provide significant improvements over existing molecular assays targeting AGM. The assays presented here can identify all three L. dispar subspecies (including the European gypsy moth, L. dispar dispar), the three other Lymantria species comprising the AGM complex, plus five additional Lymantria species that pose a threat to forests in North America. The suite of assays is built as a “molecular key” (analogous to a taxonomic key) and involves several parallel singleplex and multiplex qPCR reactions. Each reaction uses a combination of primers and probes designed to separate taxa through discriminatory annealing. The success of these assays is based on the presence of single nucleotide polymorphisms (SNPs) in the 5’ region of mitochondrial cytochrome c oxidase I (COI) or in its longer, 3’ region, as well as on the presence of an indel in the “FS1” nuclear marker, generating North American and Asian alleles, used here to assess Asian introgression into L. dispar dispar. These assays have the advantage of providing rapid and accurate identification of ten Lymantria species and subspecies considered potential FIAS.

Increasing genomic diversity and evidence of constrained lifestyle evolution due to insertion sequences in Aeromonas salmonicida

BACKGROUND

Aeromonads make up a group of Gram-negative bacteria that includes human and fish pathogens. The Aeromonas salmonicida species has the peculiarity of including five known subspecies. However, few studies of the genomes of A. salmonicida subspecies have been reported to date.

RESULTS

We sequenced the genomes of additional A. salmonicida isolates, including three from India, using next-generation sequencing in order to gain a better understanding of the genomic and phylogenetic links between A. salmonicida subspecies. Their relative phylogenetic positions were confirmed by a core genome phylogeny based on 1645 gene sequences. The Indian isolates, which formed a sub-group together with A. salmonicida subsp. pectinolytica, were able to grow at either at 18 °C and 37 °C, unlike the A. salmonicida psychrophilic isolates that did not grow at 37 °C. Amino acid frequencies, GC content, tRNA composition, loss and gain of genes during evolution, pseudogenes as well as genes under positive selection and the mobilome were studied to explain this intraspecies dichotomy.

CONCLUSION

Insertion sequences appeared to be an important driving force that locked the psychrophilic strains into their particular lifestyle in order to conserve their genomic integrity. This observation, based on comparative genomics, is in agreement with previous results showing that insertion sequence mobility induced by heat in A. salmonicida subspecies causes genomic plasticity, resulting in a deleterious effect on the virulence of the bacterium. We provide a proof-of-concept that selfish DNAs play a major role in the evolution of bacterial species by modeling genomes.

Comparative genomics and biological characterization of sequential Pseudomonas aeruginosa isolates from persistent airways infection

BACKGROUND

Pseudomonas aeruginosa establishes life-long chronic airway infections in cystic fibrosis (CF) patients. As the disease progresses, P. aeruginosa pathoadaptive variants are distinguished from the initially acquired strain. However, the genetic basis and the biology of host-bacteria interactions leading to a persistent lifestyle of P. aeruginosa are not understood. As a model system to study long term and persistent CF infections, the P. aeruginosa RP73, isolated 16.9 years after the onset of airways colonization from a CF patient, was investigated. Comparisons with strains RP1, isolated at the onset of the colonization, and clonal RP45, isolated 7 years before RP73 were carried out to better characterize genomic evolution of P. aeruginosa in the context of CF pathogenicity.

RESULTS

Virulence assessments in disease animal model, genome sequencing and comparative genomics analysis were performed for clinical RP73, RP45, RP1 and prototype strains. In murine model, RP73 showed lower lethality and a remarkable capability of long-term persistence in chronic airways infection when compared to other strains. Pathological analysis of murine lungs confirmed advanced chronic pulmonary disease, inflammation and mucus secretory cells hyperplasia. Genomic analysis predicted twelve genomic islands in the RP73 genome, some of which distinguished RP73 from other prototype strains and corresponded to regions of genome plasticity. Further, comparative genomic analyses with sequential RP isolates showed signatures of pathoadaptive mutations in virulence factors potentially linked to the development of chronic infections in CF.

CONCLUSIONS

The genome plasticity of P. aeruginosa particularly in the RP73 strain strongly indicated that these alterations may form the genetic basis defining host-bacteria interactions leading to a persistent lifestyle in human lungs.

Clinical utilization of genomics data produced by the international Pseudomonas aeruginosa consortium

The International Pseudomonas aeruginosa Consortium is sequencing over 1000 genomes and building an analysis pipeline for the study of Pseudomonas genome evolution, antibiotic resistance and virulence genes. Metadata, including genomic and phenotypic data for each isolate of the collection, are available through the International Pseudomonas Consortium Database (http://ipcd.ibis.ulaval.ca/). Here, we present our strategy and the results that emerged from the analysis of the first 389 genomes. With as yet unmatched resolution, our results confirm that P. aeruginosa strains can be divided into three major groups that are further divided into subgroups, some not previously reported in the literature. We also provide the first snapshot of P. aeruginosa strain diversity with respect to antibiotic resistance. Our approach will allow us to draw potential links between environmental strains and those implicated in human and animal infections, understand how patients become infected and how the infection evolves over time as well as identify prognostic markers for better evidence-based decisions on patient care.

Effect of estetrol on Beta-Endorphin level in female rats

INTRODUCTION

Estetrol (E4), a naturally occurring estrogen produced exclusively by human fetal liver, is currently being evaluated for potential use in contraception and menopausal care in humans. The present study was designed to profile E4 effects on the central nervous system, to assess the in vivo effects of E4 administration on Beta-Endorphin (β-END) release in specific brain structures and to evaluate whether E4 has synergic or antagonistic effects on estradiol-mediated β-END synthesis.

EXPERIMENTAL

Intact female adult rats received different doses of E4 and ovariectomized (OVX) rats received different doses of E4 or E2V or combinations of both drugs. The concentrations of β-END were assessed in the frontal and parietal cortex, hippocampus, hypothalamus, neurointermediate lobe, anterior pituitary and plasma.

RESULTS

E4 at the dose of 1mg/kg/day did not alter β-END content in most brain areas, as well as, plasma levels of intact animals E4 administered at a dose of 5mg/kg/day decreased β-END content in the hippocampus, hypothalamus, and in the neurointermediate lobe, as well as, plasma levels, compared to intact animals receiving vehicle. E4 increased β-END values in the frontal cortex, but not in the plasma, following the administration of 1mg/kg/day in OVX rats, whereas treatment with 5mg/kg/day in OVX rats induced a significant increase in β-END levels in most brain areas and in the plasma. However, in the presence of estradiol, E4 showed an estrogen-antagonistic effect in selected brain structures at the dose of 5mg/kg/day and in plasma levels of β-END at the dose of 1mg/kg/day and 5mg/kg/day.

CONCLUSION

In OVX rats, E4 increases CNS and peripheral levels of β-END, behaving as a weak estrogen-agonist. The antagonistic effect observed after combined estradiol and E4 administration further profiles E4 as a natural SERM.

Turnover of protein phosphorylation evolving under stabilizing selection

Most proteins are regulated by posttranslational modifications and changes in these modifications contribute to evolutionary changes as well as to human diseases. Phosphorylation of serines, threonines, and tyrosines are the most common modifications identified to date in eukaryotic proteomes. While the mode of action and the function of most phosphorylation sites remain unknown, functional studies have shown that phosphorylation affects protein stability, localization and ability to interact. Two broad modes of action have been described for protein phosphorylation. The first mode corresponds to the canonical and qualitative view whereby single phosphorylation sites act as molecular switches that either turn on or off specific protein functions through direct or allosteric effects. The second mode is more akin to a rheostat than a switch. In this case, a group of phosphorylation sites in a given protein region contributes collectively to the modification of the protein, irrespective of the precise position of individual sites, through an aggregate property. Here we discuss these two types of regulation and examine how they affect the rate and patterns of protein phosphorylation evolution. We describe how the evolution of clusters of phosphorylation sites can be studied under the framework of complex traits evolution and stabilizing selection.

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.

Evaluation of adhesions after laparoscopic myomectomy using the Harmonic Ace and the auto-crosslinked hyaluronan gel vs Ringer's lactate solution

OBJECTIVE

To evaluate the efficacy of a crosslinked hyaluronic acid (HA) for the prevention of postsurgical adhesions after laparoscopic myomectomy using the Harmonic Ace.

MATERIALS AND METHODS

Women 23-42 years of age who wished to conceive underwent laparoscopic myomectomy. As adhesion preventing agents, crosslinked HA gel was applied on the myometrial scar at the end of the surgery in Group A, whereas in Group B a Ringer's lactate solution was used in a prospective, observational study. Second-look mini-laparoscopy was performed 45-60 days after surgery and the adhesions were assessed according to a site-specific modified scoring.

RESULTS

The incidence of postoperative adhesions was the same in both groups, but anatomically significant adhesions and site-specific modified score was significantly reduced in Group A compared to Group B control group (31.8% vs 54.6% and 1.05 +/- 1 vs 2.27 +/- 2.5, respectively).

CONCLUSION

The use of auto-cross-linked HA gel confirms a protection on adhesion formation on myometrial wounds, although the degree of this effect appears to be weak. The absence of adnexa adhesions using the HA and a different uterine incision appear remarkable, although a larger number of patients is required to confirm the present findings.

Fertility and endocrine outcome after robot-assisted laparoscopic myomectomy (RALM)

INTRODUCTION

Laparoscopic myomectomy has recently gained wide acceptance but this procedure remains technically highly demanding and concerns have been raised about the increased blood loss and an higher risk of postoperative uterine rupture of the pregnant uterus.

OBJECTIVE

The aim of the present study is to evaluate the fertility and endocrine outcome in women underwent robot-assisted laparoscopic myomectomy (RALM).

METHODS

Data from 48 RALM performed in our department between the years 2007 and 2011 have been collected. Conception rate, abortion rate, incidence of feto-maternal morbidity or severe pregnancy and labor-related complications were reported; FSH and AMH levels and ultrasound valuation of AFC has been made before and 6 months after operation. Number of cesarean sections and vaginal deliveries were described.

RESULTS

The average age of the patients was 35 years and median Body Mass Index was 23 kg/m(2) (range 18-35 kg/m(2)). Seven women (13%) became pregnant after RALM with eight pregnancies. One pregnancy is actually on going; there were six deliveries with caesarian section and one spontaneous delivery. No spontaneous abortions. No uterine ruptures occurred. No significant modification of ovarian function was found after myomectomy.

CONCLUSION

RALM seems to have a favorable impact on the reproductive outcome of young patients with no impact on the ovarian function.

qPCA: a scalable assay to measure the perturbation of protein-protein interactions in living cells

One of the most important challenges in systems biology is to understand how cells respond to genetic and environmental perturbations. Here we show that the yeast DHFR-PCA, coupled with high-resolution growth profiling (DHFR-qPCA), is a straightforward assay to study the modulation of protein-protein interactions (PPIs) in vivo as a response to genetic, metabolic and drug perturbations. Using the canonical Protein Kinase A (PKA) pathway as a test system, we show that changes in PKA activity can be measured in living cells as a modulation of the interaction between its regulatory (Bcy1) and catalytic (Tpk1 and Tpk2) subunits in response to changes in carbon metabolism, caffeine and methyl methanesulfonate (MMS) treatments and to modifications in the dosage of its enzymatic regulators, the phosphodiesterases. Our results show that the DHFR-qPCA is easily implementable and amenable to high-throughput. The DHFR-qPCA will pave the way to the study of the effects of drug, genetic and environmental perturbations on in vivo PPI networks, thus allowing the exploration of new spaces of the eukaryotic interactome.

Evaluation of brain-derived neurotrophic factor in menstrual blood and its identification in human endometrium

The presence of high-affinity brain-derived neurotrophic factor receptor Trk B in mouse and in human fetal oocytes, together with the presence of neurotrophins in human follicular fluid suggests a paracrine role for brain-derived neurotrophic factor (BDNF) in female biology. This study aims to evaluate if BDNF is present and quantitatively determined in human menstrual blood and endometrium. Twenty-one women were studied and subdivided in two groups: A, 11 fertile women (27 ± 2 days cycle length) and B, 10 anovulatory women and/or women with inadequate luteal phase (36 ± 2 days cycle length). In fertile women menstrual BDNF levels was higher than plasma (679.3 ± 92.2 vs 301.9 ± 46.7 pg/ml p <0.001). Similarly, in Group B, BDNF in menstrual blood was higher than plasma (386.1 ± 85.2 vs 166.8 ± 24.1 pg/ml p < 0.001). Moreover, both menstrual and plasma BDNF concentrations in Group A were significantly higher respect to Group B (679.3 ± 92.2 vs 386.1 ± 85.2 pg/ml p < 0.001; 301.9 ± 46.7 vs 166.8 ± 24.1 pg/ml p < 0.001). Immunohistochemistry evidence of BDNF in endometrium, during follicular and luteal phase, was also shown. The detection of BDNF in the human menstrual blood and endometrium further supports the role of this neurotrophin in female reproductive function.

Characterization of spindle checkpoint kinase Mps1 reveals domain with functional and structural similarities to tetratricopeptide repeat motifs of Bub1 and BubR1 checkpoint kinases

Kinetochore targeting of the mitotic kinases Bub1, BubR1, and Mps1 has been implicated in efficient execution of their functions in the spindle checkpoint, the self-monitoring system of the eukaryotic cell cycle that ensures chromosome segregation occurs with high fidelity. In all three kinases, kinetochore docking is mediated by the N-terminal region of the protein. Deletions within this region result in checkpoint failure and chromosome segregation defects. Here, we use an interdisciplinary approach that includes biophysical, biochemical, cell biological, and bioinformatics methods to study the N-terminal region of human Mps1. We report the identification of a tandem repeat of the tetratricopeptide repeat (TPR) motif in the N-terminal kinetochore binding region of Mps1, with close homology to the tandem TPR motif of Bub1 and BubR1. Phylogenetic analysis indicates that TPR Mps1 was acquired after the split between deutorostomes and protostomes, as it is distinguishable in chordates and echinoderms. Overexpression of TPR Mps1 resulted in decreased efficiency of both chromosome alignment and mitotic arrest, likely through displacement of endogenous Mps1 from the kinetochore and decreased Mps1 catalytic activity. Taken together, our multidisciplinary strategy provides new insights into the evolution, structural organization, and function of Mps1 N-terminal region.

Phosphorylation network rewiring by gene duplication

In a comprehensive analysis of phosphoregulatory evolution in yeast, the authors observe that phosphorylation sites tend to be lost after gene duplication and protein network turnover reshuffles kinase–substrate relationships over time.

Elucidating how complex regulatory networks have assembled during evolution requires a detailed understanding of the evolutionary dynamics that follow gene duplication events, including changes in post-translational modifications. We compared the phosphorylation profiles of paralogous proteins in the budding yeast Saccharomyces cerevisiae to that of a species that diverged from the budding yeast before the duplication of those genes. We found that 100 million years of post-duplication divergence are sufficient for the majority of phosphorylation sites to be lost or gained in one paralog or the other, with a strong bias toward losses. However, some losses may be partly compensated for by the evolution of other phosphosites, as paralogous proteins tend to preserve similar numbers of phosphosites over time. We also found that up to 50% of kinase–substrate relationships may have been rewired during this period. Our results suggest that after gene duplication, proteins tend to subfunctionalize at the level of post-translational regulation and that even when phosphosites are preserved, there is a turnover of the kinases that phosphorylate them.

Biodiversity matters in a changing world

It is now widely accepted that the climate of our planet is changing, but it is still hard to predict the consequences of these changes on ecosystems. The impact is worst at the poles, with scientists concerned that impacts at lower latitudes will follow suit. Canada has a great responsibility and potential for studying the effects of climate changes on the ecological dynamics, given its geographical location and its scientific leadership in this field. The 5th annual meeting of the Canadian Society for Ecology and Evolution was held in the International Year of Biodiversity, to share recent advances in a wide variety of disciplines ranging from molecular biology to behavioural ecology, and to integrate them into a general view that will help us preserve biodiversity and limit the impact of climate change on ecosystems.

Influence of endogenous and exogenous sex hormones on plasma brain-derived neurotrophic factor

BACKGROUND

Brain-derived neurotrophic factor (BDNF) is a mediator of neuronal plasticity and influences learning, memory and cognitive behaviour. The aim of this study is to assess plasma BDNF variations according to hormonal status.

METHODS

A total of 60 subjects were included: 20 fertile ovulatory women, 15 amenorrhoeic women and 25 postmenopausal women. Blood samples were collected after overnight fasting. For 5 out of the 20 fertile women, samples were collected every 2 days throughout the whole menstrual cycle. Following basal evaluation, 10 out of 25 postmenopausal women were administered a hormone replacement therapy (HRT) and reevaluated after 6 months of treatment. Plasma BDNF concentrations were measured by enzyme-linked immunosorbent assay. In fertile women, estradiol (E(2)), progesterone and gonadotrophins were also assessed.

RESULTS

In fertile women, luteal phase levels of plasma BDNF were significantly higher than follicular phase levels (P < 0.001). BDNF increased from early follicular phase up to Day 14 of the cycle, reaching a pre-ovulatory peak, similar to E(2). A second rise took place during mid-luteal phase, with a peak on Day 24. Amenorrhoeic subjects, as well as postmenopausal women, showed significantly lower plasma BDNF levels compared with fertile females (P < 0.001). BDNF was positively correlated with E(2) and progesterone and negatively correlated with menopausal age. HRT restored BDNF levels to those present in fertile women during the follicular phase.

CONCLUSIONS

Plasma BDNF levels are influenced by hormonal status. Modifications in BDNF circulating levels during the menstrual cycle suggest a potential role for gonadal sex hormones (E(2) and progesterone) in regulating neurotrophin expression.

Progesterone and progestins: effects on brain, allopregnanolone and beta-endorphin

The increased use of hormonal therapies over the last years has led to improve the knowledge of pharmacological, biochemical and metabolic properties of several progestins and their effects in target tissues, such as the central nervous system. Progesterone and synthetic progestational agents are able to modulate the synthesis and release of several neurotransmitters and neuropeptides in response to specific physiological and pathological stimuli. While these actions may relay on differential activation of progesterone receptor or recruitment of intracellular pathways, some of the differences found between synthetic progestins may depend on the specific conversion to neuroactive steroids, such as the 3-alpha, 5-alpha reduced metabolite, allopregnanolone. This is a potent endogenous steroid that rapidly affects the excitability of neurons and glia cells through direct modulation of the GABA-A receptors activity exerting hypnotic/sedative, anxiolytic, anaesthetic and anticonvulsive properties. Estrogens increase the CNS and serum levels of allopregnanolone and the addition of certain but not all synthetic progestins determines a further increase in allopregnanolone levels, suggesting that the metabolism into this reduced product is related to the chemical structure of progestin molecule used. In addition, depending on specific progestin molecule used, different interaction are found with the estradiol-induced beta-endorphin synthesis and release, showing that diverse progestins have specific and divergent actions on the opiatergic system. These results highlight the concept that natural and synthetic progesterone receptor agonists may systematically induce different biological actions in CNS. This may have far-reaching implications for the clinical effects and related indications of each compound.