Gustavo C. Cerqueira

Genetic loci associated with delayed clearance of Plasmodium falciparum following artemisinin treatment in Southeast Asia

The recent emergence of artemisinin-resistant Plasmodium falciparum malaria in western Cambodia could threaten prospects for malaria elimination. Identification of the genetic basis of resistance would provide tools for molecular surveillance, aiding efforts to contain resistance. Clinical trials of artesunate efficacy were conducted in Bangladesh, in northwestern Thailand near the Myanmar border, and at two sites in western Cambodia. Parasites collected from trial participants were genotyped at 8,079 single nucleotide polymorphisms (SNPs) using a P. falciparum-specific SNP array. Parasite genotypes were examined for signatures of recent positive selection and association with parasite clearance phenotypes to identify regions of the genome associated with artemisinin resistance. Four SNPs on chromosomes 10 (one), 13 (two), and 14 (one) were significantly associated with delayed parasite clearance. The two SNPs on chromosome 13 are in a region of the genome that appears to be under strong recent positive selection in Cambodia. The SNPs on chromosomes 10 and 13 lie in or near genes involved in postreplication repair, a DNA damage-tolerance pathway. Replication and validation studies are needed to refine the location of loci responsible for artemisinin resistance and to understand the mechanism behind it; however, two SNPs on chromosomes 10 and 13 may be useful markers of delayed parasite clearance in surveillance for artemisinin resistance in Southeast Asia.

The Aspergillus Genome Database: multispecies curation and incorporation of RNA-Seq data to improve structural gene annotations

The Aspergillus Genome Database (AspGD; http://www.aspgd.org) is a freely available web-based resource that was designed for Aspergillus researchers and is also a valuable source of information for the entire fungal research community. In addition to being a repository and central point of access to genome, transcriptome and polymorphism data, AspGD hosts a comprehensive comparative genomics toolbox that facilitates the exploration of precomputed orthologs among the 20 currently available Aspergillus genomes. AspGD curators perform gene product annotation based on review of the literature for four key Aspergillus species: Aspergillus nidulans, Aspergillus oryzae, Aspergillus fumigatus and Aspergillus niger. We have iteratively improved the structural annotation of Aspergillus genomes through the analysis of publicly available transcription data, mostly expressed sequenced tags, as described in a previous NAR Database article (Arnaud et al. 2012). In this update, we report substantive structural annotation improvements for A. nidulans, A. oryzae and A. fumigatus genomes based on recently available RNA-Seq data. Over 26 000 loci were updated across these species; although those primarily comprise the addition and extension of untranslated regions (UTRs), the new analysis also enabled over 1000 modifications affecting the coding sequence of genes in each target genome.

Comprehensive annotation of secondary metabolite biosynthetic genes and gene clusters of Aspergillus nidulans, A. fumigatus, A. niger and A. oryzae

BackgroundSecondary metabolite production, a hallmark of filamentous fungi, is an expanding area of research for the Aspergilli. These compounds are potent chemicals, ranging from deadly toxins to therapeutic antibiotics to potential anti-cancer drugs. The genome sequences for multiple Aspergilli have been determined, and provide a wealth of predictive information about secondary metabolite production. Sequence analysis and gene overexpression strategies have enabled the discovery of novel secondary metabolites and the genes involved in their biosynthesis. The Aspergillus Genome Database (AspGD) provides a central repository for gene annotation and protein information for Aspergillus species. These annotations include Gene Ontology (GO) terms, phenotype data, gene names and descriptions and they are crucial for interpreting both small- and large-scale data and for aiding in the design of new experiments that further Aspergillus research.ResultsWe have manually curated Biological Process GO annotations for all genes in AspGD with recorded functions in secondary metabolite production, adding new GO terms that specifically describe each secondary metabolite. We then leveraged these new annotations to predict roles in secondary metabolism for genes lacking experimental characterization. As a starting point for manually annotating Aspergillus secondary metabolite gene clusters, we used antiSMASH (antibiotics and Secondary Metabolite Analysis SHell) and SMURF (Secondary Metabolite Unknown Regions Finder) algorithms to identify potential clusters in A. nidulans, A. fumigatus, A. niger and A. oryzae, which we subsequently refined through manual curation.ConclusionsThis set of 266 manually curated secondary metabolite gene clusters will facilitate the investigation of novel Aspergillus secondary metabolites.

The Aspergillus Genome Database (AspGD): recent developments in comprehensive multispecies curation, comparative genomics and community resources

The Aspergillus Genome Database (AspGD; http://www.aspgd.org) is a freely available, web-based resource for researchers studying fungi of the genus Aspergillus, which includes organisms of clinical, agricultural and industrial importance. AspGD curators have now completed comprehensive review of the entire published literature about Aspergillus nidulans and Aspergillus fumigatus, and this annotation is provided with streamlined, ortholog-based navigation of the multispecies information. AspGD facilitates comparative genomics by providing a full-featured genomics viewer, as well as matched and standardized sets of genomic information for the sequenced aspergilli. AspGD also provides resources to foster interaction and dissemination of community information and resources. We welcome and encourage feedback at aspergillus-curator@lists.stanford.edu.

The Genomic Diversification of the Whole Acinetobacter Genus: Origins, Mechanisms, and Consequences

Bacterial genomics has greatly expanded our understanding of microdiversification patterns within a species, but analyses at higher taxonomical levels are necessary to understand and predict the independent rise of pathogens in a genus. We have sampled, sequenced, and assessed the diversity of genomes of validly named and tentative species of the Acinetobacter genus, a clade including major nosocomial pathogens and biotechnologically important species. We inferred a robust global phylogeny and delimited several new putative species. The genus is very ancient and extremely diverse: Genomes of highly divergent species share more orthologs than certain strains within a species. We systematically characterized elements and mechanisms driving genome diversification, such as conjugative elements, insertion sequences, and natural transformation. We found many error-prone polymerases that may play a role in resistance to toxins, antibiotics, and in the generation of genetic variation. Surprisingly, temperate phages, poorly studied in Acinetobacter, were found to account for a significant fraction of most genomes. Accordingly, many genomes encode clustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems with some of the largest CRISPR-arrays found so far in bacteria. Integrons are strongly overrepresented in Acinetobacter baumannii, which correlates with its frequent resistance to antibiotics. Our data suggest that A. baumannii arose from an ancient population bottleneck followed by population expansion under strong purifying selection. The outstanding diversification of the species occurred largely by horizontal transfer, including some allelic recombination, at specific hotspots preferentially located close to the replication terminus. Our work sets a quantitative basis to understand the diversification of Acinetobacter into emerging resistant and versatile pathogens.

New resources for functional analysis of omics data for the genus Aspergillus

BackgroundDetailed and comprehensive genome annotation can be considered a prerequisite for effective analysis and interpretation of omics data. As such, Gene Ontology (GO) annotation has become a well accepted framework for functional annotation. The genus Aspergillus comprises fungal species that are important model organisms, plant and human pathogens as well as industrial workhorses. However, GO annotation based on both computational predictions and extended manual curation has so far only been available for one of its species, namely A. nidulans.ResultsBased on protein homology, we mapped 97% of the 3,498 GO annotated A. nidulans genes to at least one of seven other Aspergillus species: A. niger, A. fumigatus, A. flavus, A. clavatus, A. terreus, A. oryzae and Neosartorya fischeri. GO annotation files compatible with diverse publicly available tools have been generated and deposited online. To further improve their accessibility, we developed a web application for GO enrichment analysis named FetGOat and integrated GO annotations for all Aspergillus species with public genome sequences. Both the annotation files and the web application FetGOat are accessible via the Broad Institutes website (http://www.broadinstitute.org/fetgoat/index.html). To demonstrate the value of those new resources for functional analysis of omics data for the genus Aspergillus, we performed two case studies analyzing microarray data recently published for A. nidulans, A. niger and A. oryzae.ConclusionsWe mapped A. nidulans GO annotation to seven other Aspergilli. By depositing the newly mapped GO annotation online as well as integrating it into the web tool FetGOat, we provide new, valuable and easily accessible resources for omics data analysis and interpretation for the genus Aspergillus. Furthermore, we have given a general example of how a well annotated genome can help improving GO annotation of related species to subsequently facilitate the interpretation of omics data.

Longitudinal genomic surveillance of Plasmodium falciparum malaria parasites reveals complex genomic architecture of emerging artemisinin resistance

BackgroundArtemisinin-based combination therapies are the first line of treatment for Plasmodium falciparum infections worldwide, but artemisinin resistance has risen rapidly in Southeast Asia over the past decade. Mutations in the kelch13 gene have been implicated in this resistance. We used longitudinal genomic surveillance to detect signals in kelch13 and other loci that contribute to artemisinin or partner drug resistance. We retrospectively sequenced the genomes of 194 P. falciparum isolates from five sites in Northwest Thailand, over the period of a rapid increase in the emergence of artemisinin resistance (2001–2014).ResultsWe evaluate statistical metrics for temporal change in the frequency of individual SNPs, assuming that SNPs associated with resistance increase in frequency over this period. After Kelch13-C580Y, the strongest temporal change is seen at a SNP in phosphatidylinositol 4-kinase, which is involved in a pathway recently implicated in artemisinin resistance. Furthermore, other loci exhibit strong temporal signatures which warrant further investigation for involvement in artemisinin resistance evolution. Through genome-wide association analysis we identify a variant in a kelch domain-containing gene on chromosome 10 that may epistatically modulate artemisinin resistance.ConclusionsThis analysis demonstrates the potential of a longitudinal genomic surveillance approach to detect resistance-associated gene loci to improve our mechanistic understanding of how resistance develops. Evidence for additional genomic regions outside of the kelch13 locus associated with artemisinin-resistant parasites may yield new molecular markers for resistance surveillance, which may be useful in efforts to reduce the emergence or spread of artemisinin resistance in African parasite populations.

Discovery of McrA, a master regulator of Aspergillus secondary metabolism

Fungal secondary metabolites (SMs) are extremely important in medicine and agriculture, but regulation of their biosynthesis is incompletely understood. We have developed a genetic screen in Aspergillus nidulans for negative regulators of fungal SM gene clusters and we have used this screen to isolate mutations that upregulate transcription of the non‐ribosomal peptide synthetase gene required for nidulanin A biosynthesis. Several of these mutations are allelic and we have identified the mutant gene by genome sequencing. The gene, which we designate mcrA, is conserved but uncharacterized, and it encodes a putative transcription factor. Metabolite profiles of mcrA deletant, mcrA overexpressing, and parental strains reveal that mcrA regulates at least ten SM gene clusters. Deletion of mcrA stimulates SM production even in strains carrying a deletion of the SM regulator laeA, and deletion of mcrA homologs in Aspergillus terreus and Penicillum canescens alters the secondary metabolite profile of these organisms. Deleting mcrA in a genetic dereplication strain has allowed us to discover two novel compounds as well as an antibiotic not known to be produced by A. nidulans. Deletion of mcrA upregulates transcription of hundreds of genes including many that are involved in secondary metabolism, while downregulating a smaller number of genes.

Quantifying connectivity between local Plasmodium falciparum malaria parasite populations using identity by descent

With the rapidly increasing abundance and accessibility of genomic data, there is a growing interest in using population genetic approaches to characterize fine-scale dispersal of organisms, providing insight into biological processes across a broad range of fields including ecology, evolution and epidemiology. For sexually recombining haploid organisms such as the human malaria parasite P. falciparum, however, there have been no systematic assessments of the type of data and methods required to resolve fine scale connectivity. This analytical gap hinders the use of genomics for understanding local transmission patterns, a crucial goal for policy makers charged with eliminating this important human pathogen. Here we use data collected from four clinics with a catchment area spanning approximately 120 km of the Thai-Myanmar border to compare the ability of divergence (FST) and relatedness based on identity by descent (IBD) to resolve spatial connectivity between malaria parasites collected from proximal clinics. We found no relationship between inter-clinic distance and FST, likely due to sampling of highly related parasites within clinics, but a significant decline in IBD-based relatedness with increasing inter-clinic distance. This association was contingent upon the data set type and size. We estimated that approximately 147 single-infection whole genome sequenced parasite samples or 222 single-infection parasite samples genotyped at 93 single nucleotide polymorphisms (SNPs) were sufficient to recover a robust spatial trend estimate at this scale. In summary, surveillance efforts cannot rely on classical measures of genetic divergence to measure P. falciparum transmission on a local scale. Given adequate sampling, IBD-based relatedness provides a useful alternative, and robust trends can be obtained from parasite samples genotyped at approximately 100 SNPs.

DIVERGENOME: a bioinformatics platform to assist population genetics and genetic epidemiology studies.

Large‐scale genomics initiatives such as the HapMap project and the 1000‐genomes rely on powerful bioinformatics support to assist data production and analysis. Contrastingly, few bioinformatics platforms oriented to smaller research groups exist to store, handle, share, and integrate data from different sources, as well as to assist these scientists to perform their analyses efficiently. We developed such a bioinformatics platform, DIVERGENOME, to assist population genetics and genetic epidemiology studies performed by small‐ to medium‐sized research groups. The platform is composed of two integrated components, a relational database (DIVERGENOMEdb), and a set of tools to convert data formats as required by popular software in population genetics and genetic epidemiology (DIVERGENOMEtools). In DIVERGENOMEdb, information on genotypes, polymorphism, laboratory protocols, individuals, populations, and phenotypes is organized in projects. These can be queried according to permissions. Here, we validated DIVERGENOME through a use case regarding the analysis of SLC2A4 genetic diversity in human populations. DIVERGENOME, with its intuitive Web interface and automatic data loading capability, facilitates its use by individuals without bioinformatics background, allowing complex queries to be easily interrogated and straightforward data format conversions (not available in similar platforms). DIVERGENOME is open source, freely available, and can be accessed online (pggenetica.icb.ufmg.br/divergenome) or hosted locally. Genet. Epidemiol. 36:360–367, 2012.