Microreact

Carbapenem-resistant Klebsiella pneumoniae (CRKP) has emerged as a major clinical and public health threat. The rapid dissemination of this pathogen is driven by several successful clones worldwide. We aimed to investigate the CRKP clonal lineages, their antibiotic resistance determinants and their potential transmissions in a tertiary care hospital located in Athens, Greece. Between 2003 and 2018, 392 CRKP isolates from bloodstream infections were recovered from hospitalized patients. Whole genome sequencing (WGS) was performed on the Illumina platform to characterize 209 of these isolates. In total, 74 % (n=155) of 209 isolates belonged to three major clonal lineages: ST258 (n=108), ST147 (n=29) and ST11 (n=18). Acquired carbapenemase genes were the mechanisms of resistance in 205 isolates (bla KPC, n=123; bla VIM, n=56; bla NDM, n=20; bla OXA-48, n=6). Strong associations (P=0.0004) were observed between carbapenemase genes and clonal lineages. We first isolated bla VIM-1-carrying ST147 strains during the early sampling period in 2003, followed by the emergence of bla KPC-2-carrying ST258 in 2006 and bla NDM-1-carrying ST11 in 2013. Analysis of genetic distances between the isolates revealed six potential transmission events. When contextualizing the current collection with published data, ST147 reflected the global diversity, ST258 clustered with isolates representing the first introduction into Europe and ST11 formed a distinct geographically restricted lineage indicative of local spread. This study demonstrates the changing profile of bloodstream CRKP in a tertiary care hospital over a 15 year period and underlines the need for continued genomic surveys to develop strategies to contain further dissemination. This article contains data hosted by Microreact.

Antimicrobial resistance (AMR) mechanisms, especially those conferring resistance to critically important antibiotics, are a great concern for public health. 16S rRNA methyltransferases (16S-RMTases) abolish the effectiveness of most clinically used aminoglycosides, but some of them are considered sporadic, such as RmtE. The main goals of this work were the genomic analysis of bacteria producing 16S-RMTases from a ‘One Health’ perspective in Venezuela, and the study of the epidemiological and evolutionary scenario of RmtE variants and their related mobile genetic elements (MGEs) worldwide. A total of 21 samples were collected in 2014 from different animal and environmental sources in the Cumaná region (Venezuela). Highly aminoglycoside-resistant Enterobacteriaceae isolates were selected, identified and screened for 16S-RMTase genes. Illumina and Nanopore whole-genome sequencing data were combined to obtain hybrid assemblies and analyse their sequence type, resistome, plasmidome and pan-genome. Genomic collections of rmtE variants and their associated MGEs were generated to perform epidemiological and phylogenetic analyses. A single 16S-RMTase, the novel RmtE4, was identified in five Klebsiella isolates from wastewater samples of Cumaná. This variant possessed three amino acid modifications with respect to RmtE1–3 (Asn152Asp, Val216Ile and Lys267Ile), representing the most genetic distant among all known and novel variants described in this work, and the second most prevalent. rmtE variants were globally spread, and their geographical distribution was determined by the associated MGEs and the carrying bacterial species. Thus, rmtE4 was found to be confined to Klebsiella isolates from South America, where it was closely related to ISVsa3 and an uncommon IncL plasmid related with hospital environments. This work uncovered the global scenario of RmtE and the existence of RmtE4, which could potentially emerge from South America. Surveillance and control measures should be developed based on these findings in order to prevent the dissemination of this AMR mechanism and preserve public health worldwide.

Escherichia coli bloodstream infections are typically attributed to a limited number of lineages that carry virulence factors associated with invasiveness. In Nigeria, the identity of circulating clones is largely unknown and surveillance of their antimicrobial resistance has been limited. We verified and whole-genome sequenced 68 2016–2018 bloodstream E. coli isolates from three sentinel sites in South-Western Nigeria and susceptibility tested 67 of them. Resistance to antimicrobials commonly used in Nigeria was high, with 67 (100 %), 62 (92.5 %), 53 (79.1 %) and 37 (55.2 %) showing resistance to trimethoprim, ampicillin, ciprofloxacin and aminoglycosides, respectively. Thirty-five (51 %) isolates carried extended-spectrum β-lactamase genes and 32 (91 %) of these were multidrug resistant. All the isolates were susceptible to carbapenems and colistin. The strain set included globally disseminated high-risk clones from sequence type (ST)12 (2), ST131 (12) and ST648 (4). Twenty-three (33.8 %) of the isolates clustered within two clades. The first of these consisted of ST131 strains, comprising O16:H5 and O25:H4 sub-lineages. The second was an ST10–ST167 complex clade comprising strains carrying O-antigen and capsular genes of likely Klebsiella origin, identical to those of avian pathogenic E. coli Sanji, and serotyped in silico as O89, O101 or ONovel32, depending on the tool used. Four temporally associated ST90 strains from one sentinel were closely related enough to suggest that at least some of them represented a retrospectively detected outbreak cluster. Our data implicate a broad repertoire of E. coli isolates associated with bloodstream infections in South-West Nigeria. Continued genomic surveillance is valuable for tracking clones of importance and for outbreak identification.

Escherichia coli and Klebsiella spp. are important human pathogens that cause a wide spectrum of clinical disease. In healthcare settings, sinks and other wastewater sites have been shown to be reservoirs of antimicrobial-resistant E. coli and Klebsiella spp., particularly in the context of outbreaks of resistant strains amongst patients. Without focusing exclusively on resistance markers or a clinical outbreak, we demonstrate that many hospital sink drains are abundantly and persistently colonized with diverse populations of E. coli , Klebsiella pneumoniae and Klebsiella oxytoca , including both antimicrobial-resistant and susceptible strains. Using whole-genome sequencing of 439 isolates, we show that environmental bacterial populations are largely structured by ward and sink, with only a handful of lineages, such as E. coli ST635, being widely distributed, suggesting different prevailing ecologies, which may vary as a result of different inputs and selection pressures. Whole-genome sequencing of 46 contemporaneous patient isolates identified one (2 %; 95 % CI 0.05–11 %) E. coli urine infection-associated isolate with high similarity to a prior sink isolate, suggesting that sinks may contribute to up to 10 % of infections caused by these organisms in patients on the ward over the same timeframe. Using metagenomics from 20 sink-timepoints, we show that sinks also harbour many clinically relevant antimicrobial resistance genes including bla CTX-M, bla SHV and mcr, and may act as niches for the exchange and amplification of these genes. Our study reinforces the potential role of sinks in contributing to Enterobacterales infection and antimicrobial resistance in hospital patients, something that could be amenable to intervention. This article contains data hosted by Microreact.

Knowledge of pneumococcal lineages, their geographic distribution and antibiotic resistance patterns, can give insights into global pneumococcal disease. We provide interactive bioinformatic outputs to explore such topics, aiming to increase dissemination of genomic insights to the wider community, without the need for specialist training. We prepared 12 country-specific phylogenetic snapshots, and international phylogenetic snapshots of 73 common Global Pneumococcal Sequence Clusters (GPSCs) previously defined using PopPUNK, and present them in Microreact. Gene presence and absence defined using Roary, and recombination profiles derived from Gubbins are presented in Phandango for each GPSC. Temporal phylogenetic signal was assessed for each GPSC using BactDating. We provide examples of how such resources can be used. In our example use of a country-specific phylogenetic snapshot we determined that serotype 14 was observed in nine unrelated genetic backgrounds in South Africa. The international phylogenetic snapshot of GPSC9, in which most serotype 14 isolates from South Africa were observed, highlights that there were three independent sub-clusters represented by South African serotype 14 isolates. We estimated from the GPSC9-dated tree that the sub-clusters were each established in South Africa during the 1980s. We show how recombination plots allowed the identification of a 20 kb recombination spanning the capsular polysaccharide locus within GPSC97. This was consistent with a switch from serotype 6A to 19A estimated to have occured in the 1990s from the GPSC97-dated tree. Plots of gene presence/absence of resistance genes (tet, erm, cat) across the GPSC23 phylogeny were consistent with acquisition of a composite transposon. We estimated from the GPSC23-dated tree that the acquisition occurred between 1953 and 1975. Finally, we demonstrate the assignment of GPSC31 to 17 externally generated pneumococcal serotype 1 assemblies from Utah via Pathogenwatch. Most of the Utah isolates clustered within GPSC31 in a USA-specific clade with the most recent common ancestor estimated between 1958 and 1981. The resources we have provided can be used to explore to data, test hypothesis and generate new hypotheses. The accessible assignment of GPSCs allows others to contextualize their own collections beyond the data presented here.

Natural products (NPs), or specialized metabolites, are important for medicine and agriculture alike, and for the fitness of the organisms that produce them. NP genome-mining aims at extracting biosynthetic information from the genomes of microbes presumed to produce these compounds. Typically, canonical enzyme sequences from known biosynthetic systems are identified after sequence similarity searches. Despite this being an efficient process, the likelihood of identifying truly novel systems by this approach is low. To overcome this limitation, we previously introduced EvoMining, a genome-mining approach that incorporates evolutionary principles. Here, we release and use our latest EvoMining version, which includes novel visualization features and customizable databases, to analyse 42 central metabolic enzyme families (EFs) conserved throughout Actinobacteria , Cyanobacteria , Pseudomonas and Archaea. We found that expansion-and-recruitment profiles of these 42 families are lineage specific, opening the metabolic space related to ‘shell’ enzymes. These enzymes, which have been overlooked, are EFs with orthologues present in most of the genomes of a taxonomic group, but not in all. As a case study of canonical shell enzymes, we characterized the expansion and recruitment of glutamate dehydrogenase and acetolactate synthase into scytonemin biosynthesis, and into other central metabolic pathways driving Archaea and Bacteria adaptive evolution. By defining the origin and fate of enzymes, EvoMining complements traditional genome-mining approaches as an unbiased strategy and opens the door to gaining insights into the evolution of NP biosynthesis. We anticipate that EvoMining will be broadly used for evolutionary studies, and for generating predictions of unprecedented chemical scaffolds and new antibiotics. This article contains data hosted by Microreact.

Salmonella enterica serotype Kentucky can be a common causative agent of salmonellosis, usually associated with consumption of contaminated poultry. Antimicrobial resistance (AMR) to multiple drugs, including ciprofloxacin, is an emerging problem within this serotype. We used whole-genome sequencing (WGS) to investigate the phylogenetic structure and AMR content of 121 S. e nterica serotype Kentucky sequence type 198 isolates from five continents. Population structure was inferred using phylogenomic analysis and whole genomes were compared to investigate changes in gene content, with a focus on acquired AMR genes. Our analysis showed that multidrug-resistant (MDR) S. enterica serotype Kentucky isolates belonged to a single lineage, which we estimate emerged circa 1989 following the acquisition of the AMR-associated Salmonella genomic island (SGI) 1 (variant SGI1-K) conferring resistance to ampicillin, streptomycin, gentamicin, sulfamethoxazole and tetracycline. Phylogeographical analysis indicates this clone emerged in Egypt before disseminating into Northern, Southern and Western Africa, then to the Middle East, Asia and the European Union. The MDR clone has since accumulated various substitution mutations in the quinolone-resistance-determining regions (QRDRs) of DNA gyrase (gyrA) and DNA topoisomerase IV (parC), such that most strains carry three QRDR mutations which together confer resistance to ciprofloxacin. The majority of AMR genes in the S. e nterica serotype Kentucky genomes were carried either on plasmids or SGI structures. Remarkably, each genome of the MDR clone carried a different SGI1-K derivative structure; this variation could be attributed to IS26-mediated insertions and deletions, which appear to have hampered previous attempts to trace the clone’s evolution using sub-WGS resolution approaches. Several different AMR plasmids were also identified, encoding resistance to chloramphenicol, third-generation cephalosporins, carbapenems and/or azithromycin. These results indicate that most MDR S. e nterica serotype Kentucky circulating globally result from the clonal expansion of a single lineage that acquired chromosomal AMR genes 30 years ago, and has continued to diversify and accumulate additional resistances to last-line oral antimicrobials. This article contains data hosted by Microreact.

The surveillance of antimicrobial-resistant isolates has proven to be one of the most valuable tools to understand the global rise of multidrug-resistant bacterial pathogens. We report the first insights into the current situation in the Caribbean, where a pilot project to monitor antimicrobial resistance (AMR) through phenotypic resistance measurements combined with whole-genome sequencing was set up in collaboration with the Caribbean Public Health Agency (CARPHA). Our first study focused on Klebsiella pneumoniae , a highly relevant organism amongst the Gram-negative opportunistic pathogens worldwide causing hospital- and community-acquired infections. Our results show that not only carbapenem resistance, but also hypervirulent strains, are circulating in patients in the Caribbean. Our current data does not allow us to infer their prevalence in the population. We argue for the urgent need to further support AMR surveillance and stewardship in this almost uncharted territory, which can make a significant impact on the reduction of antimicrobial usage. This article contains data hosted by Microreact (https://microreact.org).

Shigella species are a major cause of gastroenteritis worldwide, and Shigella sonnei is the most common species isolated within the United States. Previous surveillance work in Pennsylvania documented increased antimicrobial resistance (AMR) in S. sonnei associated with reported illnesses. The present study examined a subset of these isolates by whole genome sequencing (WGS) to determine the relationship between domestic and international isolates, to identify genes that may be useful for identifying specific Global Lineages of S. sonnei and to test the accuracy of WGS for predicting AMR phenotype. A collection of 22 antimicrobial-resistant isolates from patients infected within the United States or while travelling internationally between 2009 and 2014 was chosen for WGS. Phylogenetic analysis revealed both international and domestic isolates were one of two previously defined Global Lineages of S. sonnei , designated Lineage II and Lineage III. Twelve of 17 alleles tested distinguish these two lineages. Lastly, genome analysis was used to identify AMR determinants. Genotypic analysis was concordant with phenotypic resistance for six of eight antibiotic classes. For aminoglycosides and trimethoprim, resistance genes were identified in two and three phenotypically sensitive isolates, respectively. This article contains data hosted by Microreact.

The standard workhorse for genomic analysis of the evolution of bacterial populations is phylogenetic modelling of mutations in the core genome. However, a notable amount of information about evolutionary and transmission processes in diverse populations can be lost unless the accessory genome is also taken into consideration. Here, we introduce panini (Pangenome Neighbour Identification for Bacterial Populations), a computationally scalable method for identifying the neighbours for each isolate in a data set using unsupervised machine learning with stochastic neighbour embedding based on the t-SNE (t-distributed stochastic neighbour embedding) algorithm. panini is browser-based and integrates with the Microreact platform for rapid online visualization and exploration of both core and accessory genome evolutionary signals, together with relevant epidemiological, geographical, temporal and other metadata. Several case studies with single- and multi-clone pneumococcal populations are presented to demonstrate the ability to identify biologically important signals from gene content data. panini is available at http://panini.pathogen.watch and code at http://gitlab.com/cgps/panini.

The ability to distinguish different circulating pathogen clones from each other is a fundamental requirement to understand the epidemiology of infectious diseases. Phylogenetic analysis of genomic data can provide a powerful platform to identify lineages within bacterial populations, and thus inform outbreak investigation and transmission dynamics. However, resolving differences between pathogens associated with low-variant (LV) populations carrying low median pairwise single nucleotide variant (SNV) distances remains a major challenge. Here we present rPinecone, an R package designed to define sub-lineages within closely related LV populations. rPinecone uses a root-to-tip directional approach to define sub-lineages within a phylogenetic tree according to SNV distance from the ancestral node. The utility of this software was demonstrated using both simulated outbreaks and real genomic data of two LV populations: a hospital outbreak of methicillin-resistant Staphylococcus aureus and endemic Salmonella Typhi from rural Cambodia. rPinecone identified the transmission branches of the hospital outbreak and geographically confined lineages in Cambodia. Sub-lineages identified by rPinecone in both analyses were phylogenetically robust. It is anticipated that rPinecone can be used to discriminate between lineages of bacteria from LV populations where other methods fail, enabling a deeper understanding of infectious disease epidemiology for public health purposes.

Gonorrhoea infections are on the increase and strains that are resistant to all antimicrobials used to treat the disease have been found worldwide. These observations encouraged the World Health Organization to include Neisseria gonorrhoeae on their list of high-priority organisms in need of new treatments. Fortunately, concurrent resistance to both antimicrobials used in dual therapy is still rare. The fight against antimicrobial resistance (AMR) must begin from an understanding of how it evolves and spreads in sexual networks. Genome-based analyses have allowed the study of the gonococcal population dynamics and transmission, giving a novel perspective on AMR gonorrhoea. Here, we will review past, present and future treatment options for gonorrhoea and explain how genomics is helping to increase our understanding of the changing AMR and transmission landscape. This article contains data hosted by Microreact.

The pathogen Flavobacterium psychrophilum is a major problem for the expanding salmonid fish farming industry in Sweden as well as worldwide. A better understanding of the phylogeography and infection routes of F. psychrophilum outbreaks could help to improve aquaculture profitability and the welfare of farmed fish while reducing the need for antibiotics. In the present study, high-throughput genome sequencing was applied to a collection of F. psychrophilum isolates (n=38) from outbreaks on fish farms in different regions of Sweden between 1988 and 2016. Antibiotic susceptibility tests were applied to a subset of the isolates and the results correlated to the presence of genetic resistance markers. We show that F. psychrophilum clones are not regionally biased and that new clones with a higher degree of antibiotic resistance have emerged nationwide during the study period. This supports previous theories of the importance of live fish and egg trade as a route of infection. Continuous monitoring of recovered isolates by high-throughput sequencing techniques in the future could facilitate tracing of clones within and between countries, as well as the detection of emergent virulent or antibiotic-resistant clones. This article contains data hosted by Microreact.

Renibacterium salmoninarum is the causative agent of bacterial kidney disease (BKD), which is a commercially important disease of farmed salmonids. Typing by conventional methods provides limited information on the evolution and spread of this pathogen, as there is a low level of standing variation within the R. salmoninarum population. Here, we apply whole-genome sequencing to 42 R. salmoninarum isolates from Chile, primarily from salmon farms, in order to understand the epidemiology of BKD in this country. The patterns of genomic variation are consistent with multiple introductions to Chile, followed by rapid dissemination over a 30 year period. The estimated dates of introduction broadly coincide with major events in the development of the Chilean aquaculture industry. We find evidence for significant barriers to transmission of BKD in the Chilean salmon production chain that may also be explained by previously undescribed signals of host tropism in R. salmoninarum. Understanding the genomic epidemiology of BKD can inform disease intervention and improve sustainability of the economically important salmon industry. This article contains data hosted by Microreact.

The implementation of pneumococcal conjugate vaccines (PCVs) has led to a decline in vaccine-type disease. However, there is evidence that the epidemiology of non-typeable Haemophilus influenzae (NTHi) carriage and disease can be altered as a consequence of PCV introduction. We explored the epidemiological shifts in NTHi carriage using whole genome sequencing over a 5-year period that included PCV13 replacement of PCV7 in the UK’s National Immunization Programme in 2010. Between 2008/09 and 2012/13 (October to March), nasopharyngeal swabs were taken from children <5 years of age. Significantly increased carriage post-PCV13 was observed and lineage-specific associations with Streptococcus pneumoniae were seen before but not after PCV13 introduction. NTHi were characterized into 11 discrete, temporally stable lineages, congruent with current knowledge regarding the clonality of NTHi. The increased carriage could not be linked to the expansion of a particular clone and different co-carriage dynamics were seen before PCV13 implementation when NTHi co-carried with vaccine serotype pneumococci. In summary, PCV13 introduction has been shown to have an indirect effect on NTHi epidemiology and there exists both negative and positive, distinct associations between pneumococci and NTHi. This should be considered when evaluating the impacts of pneumococcal vaccine design and policy.

There is growing evidence that patients with Clostridiumdifficile-associated diarrhoea often acquire their infecting strain before hospital admission. Wastewater is known to be a potential source of surface water that is contaminated with C. difficile spores. Here, we describe a study that used genome sequencing to compare C. difficile isolated from multiple wastewater treatment plants across the East of England and from patients with clinical disease at a major hospital in the same region. We confirmed that C. difficile from 65 patients were highly diverse and that most cases were not linked to other active cases in the hospital. In total, 186 C. difficile isolates were isolated from effluent water obtained from 18 municipal treatment plants at the point of release into the environment. Whole genome comparisons of clinical and environmental isolates demonstrated highly related populations, and confirmed extensive release of toxigenic C. difficile into surface waters. An analysis based on multilocus sequence types (STs) identified 19 distinct STs in the clinical collection and 38 STs in the wastewater collection, with 13 of 44 STs common to both clinical and wastewater collections. Furthermore, we identified five pairs of highly similar isolates (≤2 SNPs different in the core genome) in clinical and wastewater collections. Strategies to control community acquisition should consider the need for bacterial control of treated wastewater.

Yersinia pseudotuberculosis is a Gram-negative intestinal pathogen of humans and has been responsible for several nationwide gastrointestinal outbreaks. Large-scale population genomic studies have been performed on the other human pathogenic species of the genus Yersinia, Yersinia pestis and Yersinia enterocolitica allowing a high-resolution understanding of the ecology, evolution and dissemination of these pathogens. However, to date no purpose-designed large-scale global population genomic analysis of Y. pseudotuberculosis has been performed. Here we present analyses of the genomes of 134 strains of Y. pseudotuberculosis isolated from around the world, from multiple ecosystems since the 1960s. Our data display a phylogeographic split within the population, with an Asian ancestry and subsequent dispersal of successful clonal lineages into Europe and the rest of the world. These lineages can be differentiated by CRISPR cluster arrays, and we show that the lineages are limited with respect to inter-lineage genetic exchange. This restriction of genetic exchange maintains the discrete lineage structure in the population despite co-existence of lineages for thousands of years in multiple countries. Our data highlights how CRISPR can be informative of the evolutionary trajectory of bacterial lineages, and merits further study across bacteria.

Serotype replacement has been reported in carriage and disease after pneumococcal conjugate vaccine (PCV) introductions in the UK and globally. We previously described concurrent expansion and decline of sequence types associated with serotype replacement over 5 years following PCV introductions in the UK. Here we use whole-genome sequencing to fully characterise the population structure of pneumococcal isolates collected over seven winters encompassing PCV7 and PCV13 introductions in the UK, investigating the importance of lineages in serotype replacement. We analysed 672 pneumococcal genomes from colonised children of 4 years old or less. The temporal prevalence of 20 lineages, defined by hierarchical Bayesian analysis of population structure (BAPS), was assessed in the context of serotype replacement. Multiple serotypes were detected in the primary winter of sampling within three vaccine-type (VT) lineages BAPS4, BAPS10 and BAPS11, in which serotype replacement were observed. In contrast, serotype replacement was not seen in the remaining three VT lineages (BAPS1, BAPS13 and BAPS14), that expressed a single serotype (6B, 6A and 3, respectively) in the primary winter. One lineage, BAPS1 serotype 6B was undetectable in the population towards the end of the study period. The dynamics of serotype replacement, in this UK population, was preceded by the presence or absence of multiple serotypes within VT lineages, in the pre-PCV population. This observation could help predict which non-vaccine types (NVTs) may be involved in replacement in future PCV introductions here and elsewhere. It could further indicate whether any antibiotic resistance associated with the lineages is likely to be affected by replacement.

An epidemic of post-surgical wound infections, caused by a non-tuberculous mycobacterium, has been on-going in Brazil. It has been unclear whether one or multiple lineages are responsible and whether their wide geographical distribution across Brazil is due to spread from a single point source or is the result of human-mediated transmission. 188 isolates, collected from nine Brazilian states, were whole genome sequenced and analysed using phylogenetic and comparative genomic approaches. The isolates from Brazil formed a single clade, which was estimated to have emerged in 2003. We observed temporal and geographic structure within the lineage that enabled us to infer the movement of sub-lineages across Brazil. The genome size of the Brazilian lineage was reduced relative to most strains in the three subspecies of Mycobacterium abscessus and contained a novel plasmid, pMAB02, in addition to the previously described pMAB01 plasmid. One lineage, which emerged just prior to the initial outbreak, is responsible for the epidemic of post-surgical wound infections in Brazil. Phylogenetic analysis indicates that multiple transmission events led to its spread. The presence of a novel plasmid and the reduced genome size suggest that the lineage has undergone adaptation to the surgical niche.

Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets.