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Overcoming Data Bottlenecks in Genomic Pathogen Surveillance.

ABSTRACT: Performing whole genome sequencing (WGS) for the surveillance of antimicrobial resistance offers the ability to determine not only the antimicrobials to which rates of resistance are increasing, but also the evolutionary mechanisms and transmission routes responsible for the increase at local, national, and global scales. To derive WGS-based outputs, a series of processes are required, beginning with sample and metadata collection, followed by nucleic acid extraction, library preparation, sequencing, and analysis. Throughout this pathway there are many data-related operations required (informatics) combined with more biologically focused procedures (bioinformatics). For a laboratory aiming to implement pathogen genomics, the informatics and bioinformatics activities can be a barrier to starting on the journey; for a laboratory that has already started, these activities may become overwhelming. Here we describe these data bottlenecks and how they have been addressed in laboratories in India, Colombia, Nigeria, and the Philippines, as part of the National Institute for Health Research Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance. The approaches taken include the use of reproducible data parsing pipelines and genome sequence analysis workflows, using technologies such as Data-flo, the Nextflow workflow manager, and containerization of software dependencies. By overcoming barriers to WGS implementation in countries where genome sampling for some species may be underrepresented, a body of evidence can be built to determine the concordance of antimicrobial sensitivity testing and genome-derived resistance, and novel high-risk clones and unknown mechanisms of resistance can be discovered.

SUBMITTER: Afolayan AO

PROVIDER: S-EPMC8634317 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:UNLABELLED:With the advent of deep sequencing, genomic surveillance has become a popular method for detection of infectious disease, supplementing information gathered by classic clinical or serological techniques to identify host-determinant markers and trace the origin of transmission. However, two main factors complicate genomic surveillance. First, pathogens exhibiting high genetic diversity demand higher levels of scrutiny to obtain an accurate representation of the entire population. Second, current systems of detection are nonuniform, with significant gaps in certain geographic locations and animal reservoirs. Despite past unforeseen pandemics like the 2009 swine-origin H1N1 influenza virus, there is no standardized way of evaluating surveillance. A more complete surveillance system should capture a greater proportion of pathogen diversity. Here we present a novel quantitative method of assessing the completeness of genomic surveillance that incorporates the time of sequence collection, as well as the pathogen's evolutionary rate. We propose the q2 coefficient, which measures the proportion of sequenced isolates whose closest neighbor in the past is within a genetic distance equivalent to 2 years of evolution, roughly the median time of changing strain selection for influenza A vaccines. Easily interpretable and significantly faster than other methods, the q2 coefficient requires no full phylogenetic characterization or use of arbitrary clade definitions. Application of the q2 coefficient to influenza A virus confirmed poor sampling of swine and avian populations and identified regions with deficient surveillance. We demonstrate that the q2 coefficient can not only be applied to other pathogens, including dengue and West Nile viruses, but also used to describe surveillance dynamics, particularly the effects of different public health policies. IMPORTANCE:Surveillance programs have become key assets in determining the emergence or prevalence of pathogens circulating in human and animal populations. Genomic surveillance, in particular, provides comprehensive information on the history of isolates and potential molecular markers for infectivity and pathogenicity. Current techniques for evaluating genomic surveillance are inaccurate, ignoring the pathogen's evolutionary rate and biodiversity, as well as the timing of sequence collection. Using sequence data, we propose the q2 coefficient as a quantitative measure of surveillance completeness that combines elements of time and evolution without defining arbitrary criteria for clades or species. Through several case studies of influenza A, dengue, and West Nile viruses, we employed the q2 coefficient to identify sampling deficiencies in different host species and locations, as well as examine the effects of different public health policies through historical records of the q2 coefficient. These results can guide public health agencies to focus resource allocation and virus collection to bolster specific problems in surveillance.

Project description:Terpenoids are a large and diverse class of plant metabolites that also includes volatile mono- and sesquiterpenes which are involved in biotic interactions of plants. Due to the limited natural availability of these terpenes and the tight regulation of their biosynthesis, there is strong interest to introduce or enhance their production in crop plants by metabolic engineering for agricultural, pharmaceutical and industrial applications. While engineering of monoterpenes has been quite successful, expression of sesquiterpene synthases in engineered plants frequently resulted in production of only minor amounts of sesquiterpenes. To identify bottlenecks for sesquiterpene engineering in plants, we have used two nearly identical terpene synthases, snapdragon (Antirrhinum majus) nerolidol/linalool synthase-1 and -2 (AmNES/LIS-1/-2), that are localized in the cytosol and plastids, respectively. Since these two bifunctional terpene synthases have very similar catalytic properties with geranyl diphosphate (GPP) and farnesyl diphosphate (FPP), their expression in target tissues allows indirect determination of the availability of these substrates in both subcellular compartments. Both terpene synthases were expressed under control of the ripening specific PG promoter in tomato fruits, which are characterized by a highly active terpenoid metabolism providing precursors for carotenoid biosynthesis. As AmNES/LIS-2 fruits produced the monoterpene linalool, AmNES/LIS-1 fruits were found to exclusively produce the sesquiterpene nerolidol. While nerolidol emission in AmNES/LIS-1 fruits was 60- to 584-fold lower compared to linalool emission in AmNES/LIS-2 fruits, accumulation of nerolidol-glucosides in AmNES/LIS-1 fruits was 4- to 14-fold lower than that of linalool-glucosides in AmNES/LIS-2 fruits. These results suggest that only a relatively small pool of FPP is available for sesquiterpene formation in the cytosol. To potentially overcome limitations in sesquiterpene production, we transiently co-expressed the key pathway-enzymes hydroxymethylglutaryl-CoA reductase (HMGR) and 1-deoxy-D-xylulose 5-phosphate synthase (DXS), as well as the regulator isopentenyl phosphate kinase (IPK). While HMGR and IPK expression increased metabolic flux toward nerolidol formation 5.7- and 2.9-fold, respectively, DXS expression only resulted in a 2.5-fold increase.

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Overcoming Data Bottlenecks in Genomic Pathogen Surveillance.

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