Salinity investment framework : agricultural land and infrastructure

Greater awareness of the potential impact of salinity has led to increased public and private expenditure. The Salinity Investment Framework was developed to insert rigour and accountability into decision-making processes and guide future development. This report focusses on the economic impact of salinity on private and public land and the infrastructure of areas in Western Australia, including towns, railway systems, roads and the like

Genome-wide association, prediction and heritability in bacteria with application to Streptococcus pneumoniae

Whole-genome sequencing has facilitated genome-wide analyses of association, prediction and heritability in many organisms. However, such analyses in bacteria are still in their infancy, being limited by difficulties including genome plasticity and strong population structure. Here we propose a suite of methods including linear mixed models, elastic net and LD-score regression, adapted to bacterial traits using innovations such as frequency-based allele coding, both insertion/deletion and nucleotide testing and heritability partitioning. We compare and validate our methods against the current state-of-art using simulations, and analyse three phenotypes of the major human pathogen Streptococcus pneumoniae, including the first analyses of minimum inhibitory concentrations (MIC) for penicillin and ceftriaxone. We show that the MIC traits are highly heritable with high prediction accuracy, explained by many genetic associations under good population structure control. In ceftriaxone MIC, this is surprising because none of the isolates are resistant as per the inhibition zone criteria. We estimate that half of the heritability of penicillin MIC is explained by a known drug-resistance region, which also contributes a quarter of the ceftriaxone MIC heritability. For the within-host carriage duration phenotype, no associations were observed, but the moderate heritability and prediction accuracy indicate a moderately polygenic trait.Peer reviewe

RCandy: an R package for visualizing homologous recombinations in bacterial genomes

SUMMARY: Homologous recombination is an important evolutionary process in bacteria and other prokaryotes, which increases genomic sequence diversity and can facilitate adaptation. Several methods and tools have been developed to detect genomic regions recently affected by recombination. Exploration and visualization of such recombination events can reveal valuable biological insights, but it remains challenging. Here, we present RCandy, a platform-independent R package for rapid, simple and flexible visualization of recombination events in bacterial genomes. AVAILABILITY AND IMPLEMENTATION: RCandy is an R package freely available for use under the MIT license. It is platform-independent and has been tested on Windows, Linux and MacOSX. The source code comes together with a detailed vignette available on GitHub at https://github.com/ChrispinChaguza/RCandy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

OPR-PPR, a Computer Program for Assessing Data Importance to Model Predictions Using Linear Statistics

The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005. The method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one or more parameters is added

Pneumococcal within-host diversity during colonization, transmission and treatment

Characterizing the genetic diversity of pathogens within the host promises to greatly improve surveillance and reconstruction of transmission chains. For bacteria, it also informs our understanding of inter-strain competition and how this shapes the distribution of resistant and sensitive bacteria. Here we study the genetic diversity of Streptococcus pneumoniae within 468 infants and 145 of their mothers by deep sequencing whole pneumococcal populations from 3,761 longitudinal nasopharyngeal samples. We demonstrate that deep sequencing has unsurpassed sensitivity for detecting multiple colonization, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared with gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the child's life. Comprehensive treatment data demonstrated that infants were at an elevated risk of both the acquisition and persistent colonization of a multidrug-resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting that they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonization imply that in the absence of treatment, susceptible lineages outcompeted resistant lineages within the host. These results demonstrate the many benefits of deep sequencing for the genomic surveillance of bacterial pathogens. Longitudinal population deep sequencing of Streptococcus pneumoniae sampled from infants and their mothers improves our understanding of the dynamics of colonization, transmission, inter-strain competition and the impact of antibiotic treatment.Peer reviewe

Detecting co-selection through excess linkage disequilibrium in bacterial genomes

Population genomics has revolutionized our ability to study bacterial evolution by enabling data-driven discovery of the genetic architecture of trait variation. Genome-wide association studies (GWAS) have more recently become accompanied by genome-wide epistasis and co-selection (GWES) analysis, which offers a phenotype-free approach to generating hypotheses about selective processes that simultaneously impact multiple loci across the genome. However, existing GWES methods only consider associations between distant pairs of loci within the genome due to the strong impact of linkage-disequilibrium (LD) over short distances. Based on the general functional organisation of genomes it is nevertheless expected that majority of co-selection and epistasis will act within relatively short genomic proximity, on co-variation occurring within genes and their promoter regions, and within operons. Here, we introduce LDWeaver, which enables an exhaustive GWES across both short- and long-range LD, to disentangle likely neutral co-variation from selection. We demonstrate the ability of LDWeaver to efficiently generate hypotheses about co-selection using large genomic surveys of multiple major human bacterial pathogen species and validate several findings using functional annotation and phenotypic measurements. Our approach will facilitate the study of bacterial evolution in the light of rapidly expanding population genomic data

Absolute risk representation in cardiovascular disease prevention: comprehension and preferences of health care consumers and general practitioners involved in a focus group study

Background Communicating risk is part of primary prevention of coronary heart disease and stroke, collectively referred to as cardiovascular disease (CVD). In Australia, health organisations have promoted an absolute risk approach, thereby raising the question of suitable standardised formats for risk communication. Methods Sixteen formats of risk representation were prepared including statements, icons, graphical formats, alone or in combination, and with variable use of colours. All presented the same risk, i.e., the absolute risk for a 55 year old woman, 16% risk of CVD in five years. Preferences for a five or ten-year timeframe were explored. Australian GPs and consumers were recruited for participation in focus groups, with the data analysed thematically and preferred formats tallied. Results Three focus groups with health consumers and three with GPs were held, involving 19 consumers and 18 GPs. Consumers and GPs had similar views on which formats were more easily comprehended and which conveyed 16% risk as a high risk. A simple summation of preferences resulted in three graphical formats (thermometers, vertical bar chart) and one statement format as the top choices. The use of colour to distinguish risk (red, yellow, green) and comparative information (age, sex, smoking status) were important ingredients. Consumers found formats which combined information helpful, such as colour, effect of changing behaviour on risk, or comparison with a healthy older person. GPs preferred formats that helped them relate the information about risk of CVD to their patients, and could be used to motivate patients to change behaviour. Several formats were reported as confusing, such as a percentage risk with no contextual information, line graphs, and icons, particularly those with larger numbers. Whilst consumers and GPs shared preferences, the use of one format for all situations was not recommended. Overall, people across groups felt that risk expressed over five years was preferable to a ten-year risk, the latter being too remote. Conclusions Consumers and GPs shared preferences for risk representation formats. Both groups liked the option to combine formats and tailor the risk information to reflect a specific individual's risk, to maximise understanding and provide a good basis for discussion

Detecting co-selection through excess linkage disequilibrium in bacterial genomes

Population genomics has revolutionized our ability to study bacterial evolution by enabling data-driven discovery of the genetic architecture of trait variation. Genome-wide association studies (GWAS) have more recently become accompanied by genome-wide epistasis and co-selection (GWES) analysis, which offers a phenotype-free approach to generating hypotheses about selective processes that simultaneously impact multiple loci across the genome. However, existing GWES methods only consider associations between distant pairs of loci within the genome due to the strong impact of linkage-disequilibrium (LD) over short distances. Based on the general functional organisation of genomes it is nevertheless expected that majority of co-selection and epistasis will act within relatively short genomic proximity, on co-variation occurring within genes and their promoter regions, and within operons. Here, we introduce LDWeaver, which enables an exhaustive GWES across both short- and long-range LD, to disentangle likely neutral co-variation from selection. We demonstrate the ability of LDWeaver to efficiently generate hypotheses about co-selection using large genomic surveys of multiple major human bacterial pathogen species and validate several findings using functional annotation and phenotypic measurements. Our approach will facilitate the study of bacterial evolution in the light of rapidly expanding population genomic data

Emergence and dissemination of antimicrobial resistance in Escherichia coli causing bloodstream infections in Norway in 2002-17: a nationwide, longitudinal, microbial population genomic study.

BACKGROUND: The clonal diversity underpinning trends in multidrug resistant Escherichia coli causing bloodstream infections remains uncertain. We aimed to determine the contribution of individual clones to resistance over time, using large-scale genomics-based molecular epidemiology. METHODS: This was a longitudinal, E coli population, genomic, cohort study that sampled isolates from 22 512 E coli bloodstream infections included in the Norwegian surveillance programme on resistant microbes (NORM) from 2002 to 2017. 15 of 22 laboratories were able to share their isolates, and the first 22·5% of isolates from each year were requested. We used whole genome sequencing to infer the population structure (PopPUNK), and we investigated the clade composition of the dominant multidrug resistant clonal complex (CC)131 using genetic markers previously reported for sequence type (ST)131, effective population size (BEAST), and presence of determinants of antimicrobial resistance (ARIBA, PointFinder, and ResFinder databases) over time. We compared these features between the 2002-10 and 2011-17 time periods. We also compared our results with those of a longitudinal study from the UK done between 2001 and 2011. FINDINGS: Of the 3500 isolates requested from the participating laboratories, 3397 (97·1%) were received, of which 3254 (95·8%) were successfully sequenced and included in the analysis. A significant increase in the number of multidrug resistant CC131 isolates from 71 (5·6%) of 1277 in 2002-10 to 207 (10·5%) of 1977 in 2011-17 (p<0·0001), was the largest clonal expansion. CC131 was the most common clone in extended-spectrum β-lactamase (ESBL)-positive isolates (75 [58·6%] of 128) and fluoroquinolone non-susceptible isolates (148 [39·2%] of 378). Within CC131, clade A increased in prevalence from 2002, whereas the global multidrug resistant clade C2 was not observed until 2007. Multiple de-novo acquisitions of both blaCTX-M ESBL-encoding genes in clades A and C1 and gain of phenotypic fluoroquinolone non-susceptibility across the clade A phylogeny were observed. We estimated that exponential increases in the effective population sizes of clades A, C1, and C2 occurred in the mid-2000s, and in clade B a decade earlier. The rate of increase in the estimated effective population size of clade A (Ne=3147) was nearly ten-times that of C2 (Ne=345), with clade A over-represented in Norwegian CC131 isolates (75 [27·0%] of 278) compared with the UK study (8 [5·4%] of 147 isolates). INTERPRETATION: The early and sustained establishment of predominantly antimicrobial susceptible CC131 clade A isolates, relative to multidrug resistant clade C2 isolates, suggests that resistance is not necessary for clonal success. However, even in the low antibiotic use setting of Norway, resistance to important antimicrobial classes has rapidly been selected for in CC131 clade A isolates. This study shows the importance of genomic surveillance in uncovering the complex ecology underlying multidrug resistance dissemination and competition, which have implications for the design of strategies and interventions to control the spread of high-risk multidrug resistant clones. FUNDING: Trond Mohn Foundation, European Research Council, Marie Skłodowska-Curie Actions, and the Wellcome Trust