Mixed-species Samples Research Articles

Model Exploration and Application of Near-Infrared Spectroscopy for Species Separation and Quantification during Mixed Litter Decomposition in Subtropical Forests of China

Litter of different species coexists in the natural ecosystem and may induce non-additive effects during decomposition. Identifying and quantifying the origins of species in litter mixtures is essential for evaluating the responses of each component species when mixed with co-occurring species and then unraveling the underlying mechanism of the mixing effects of litter decomposition. Here, we used near-infrared spectroscopy (NIRS) to predict the species composition and proportions of four-tree species foliage mixtures in association with litter crude ash and litter decomposition time. To simulate the whole mixed litter decomposition process in situ, a controlled mixture of four tree species litter leaves consisting of 15 tree species combinations and 193 artificial mixed-species samples were created for model development and verification using undecomposed pure tree species and decomposed litter of single tree species over one year. Two series of NIRS models were developed with the original mass and ash-free weight as reference values. The results showed that these NIRS models could provide an accurate prediction for the percentage of the component species from in the litter leaf mixture’s composition. The predictive ability of the near-infrared spectroscopy model declined marginally with the prolonged litter decomposition time. Furthermore, the model with ash-free litter mass as a reference exhibited a higher coefficient of determination (R2) and a lower standard error of prediction (RMSECV). Thus, our results demonstrate that NIRS presents great potential for not only predicting the organic composition and proportion in multi-species mixed samples in static conditions, but also for samples in dynamic conditions (i.e., during the litter decomposition process), which could facilitate evaluation of the species-specific responses and impacts on the interspecific interactions of co-occurring species in high-biodiversity communities.

A CRISPR-based strategy for targeted sequencing in biodiversity science.

Many applications in molecular ecology require the ability to match specific DNA sequences from single- or mixed-species samples with a diagnostic reference library. Widely used methods for DNA barcoding and metabarcoding employ PCR and amplicon sequencing to identify taxa based on target sequences, but the target-specific enrichment capabilities of CRISPR-Cas systems may offer advantages in some applications. We identified 54,837 CRISPR-Cas guide RNAs that may be useful for enriching chloroplast DNA across phylogenetically diverse plant species. We tested a subset of 17 guide RNAs invitro to enrich plant DNA strands ranging in size from diagnostic DNA barcodes of 1,428 bp to entire chloroplast genomes of 121,284 bp. We used an Oxford Nanopore sequencer to evaluate sequencing success based on both single- and mixed-species samples, which yielded mean chloroplast sequence lengths of 2,530-11,367 bp, depending on the experiment. In comparison to mixed-species experiments, single-species experiments yielded more on-target sequence reads and greater mean pairwise identity between contigs and the plant species' reference genomes. But nevertheless, these mixed-species experiments yielded sufficient data to provide ≥48-fold increase in sequence length and better estimates of relative abundance for a commercially prepared mixture of plant species compared to DNA metabarcoding based on the chloroplast trnL-P6 marker. Prior work developed CRISPR-based enrichment protocols for long-read sequencing and our experiments pioneered its use for plant DNA barcoding and chloroplast assemblies that may have advantages over workflows that require PCR and short-read sequencing. Future work would benefit from continuing to develop invitro and in silico methods for CRISPR-based analyses of mixed-species samples, especially when the appropriate reference genomes for contig assembly cannot be known a priori.

Investigating the use of pollen DNA metabarcoding to quantify bee foraging and effects of threshold selection.

DNA metabarcoding of pollen is a useful tool for studying bee foraging ecology. However, several questions about this method remain unresolved, including the extent to which sequence read data is quantitative, which type of sequence count removal threshold to use and how that choice affects our ability to detect rare flower visits, and how sequence artefacts may confound conclusions about bee foraging behavior. To address these questions, we isolated pollen from five plant species and created treatments comprised of pollen from each species alone and combinations of pollen from multiple species that varied in richness and evenness. We used ITS2 and rbcL metabarcoding to identify plant species in the samples, compared the proportion of pollen by mass to the proportion of sequencing reads for each plant species in each treatment, and analyzed the sequencing data using both liberal and conservative thresholds. We collected pollen from foraging bees, analyzed metabarcoding data from those samples using each threshold, and compared the differences in the pollinator networks constructed from the data. Regardless of the threshold used, the relationship between the proportion of pollen by mass and sequencing reads was inconsistent, suggesting that the number of sequence reads is a poor proxy for pollen abundance in mixed-species samples. Using a liberal threshold resulted in greater detection of original plant species in mixtures but also detected additional species in mixtures and single-species samples. The conservative threshold reduced the number of additional plant species detected, but several species in mixtures were not detected above the threshold, resulting in false negatives. Pollinator networks produced using the two thresholds differed and illustrated tradeoffs between detection of rare species and estimation of network complexity. Threshold selection can have a major effect on conclusions drawn from studies using metabarcoding of bee pollen to study plant-pollinator interactions.

Advancing Mitochondrial Metagenomics: A New Assembly Strategy and Validating the Power of Seed-Based Approach

Mitochondrial metagenomics (MMG) using Illumina sequencers for mixed-species samples provides a promising tool for evolutionary and ecological studies using mitogenomes. However, the traditional assembly procedure is still computationally intensive and expensive. Here, a novel MMG pipeline was applied to different DNA extractions, one per species, and their sequence as a mixed sample for rapid mitogenome assembly is presented. Our method integrated a faster and more accurate read mapper for filtering non-mitochondrial reads. A seed-and-extend assembler for species-specific mitogenomes that detects ‘noisy species/sequences’ was also assessed. The MMG pipeline for each dataset was completed in a few hours on desktop PCs, maintaining high accuracy and completeness (COI divergence >10%), except for some very closely related taxa. Particularly for closely related species, the exclusion of ‘noisy reads’ (including chimera of non-targeted species) improved the target assembly. In addition, we observed that short barcodes used as references had almost identical detection power compared with mitogenomes but required greater sequencing depth. We tested our MMG pipeline on two real and one simulated dataset to validate its high efficiency in mixed-species sample mitogenome assembly.

Comparing novel shotgun DNA sequencing and state-of-the-art proteomics approaches for authentication of fish species in mixed samples

Replacement of high-value fish species with cheaper varieties or mislabelling of food unfit for human consumption is a global problem violating both consumers’ rights and safety. For distinguishing fish species in pure samples, DNA approaches are available; however, authentication and quantification of fish species in mixtures remains a challenge. In the present study, a novel high-throughput shotgun DNA sequencing approach applying masked reference libraries was developed and used for authentication and abundance calculations of fish species in mixed samples. Results demonstrate that the analytical protocol presented here can discriminate and predict relative abundances of different fish species in mixed samples with high accuracy. In addition to DNA analyses, shotgun proteomics tools based on direct spectra comparisons were employed on the same mixture. Similar to the DNA approach, the identification of individual fish species and the estimation of their respective relative abundances in a mixed sample also were feasible. Furthermore, the data obtained indicated that DNA sequencing using masked libraries predicted species-composition of the fish mixture with higher specificity, while at a taxonomic family level, relative abundances of the different species in the fish mixture were predicted with slightly higher accuracy using proteomics tools. Taken together, the results demonstrate that both DNA and protein-based approaches presented here can be used to efficiently tackle current challenges in feed and food authentication analyses.

SAMPLE COMPOSITION: PARASITE ECOLOGY'S DIRTY LITTLE SECRET.

In comparative studies, the advantage of increased sample sizes might be outweighed by detrimental effects on sample homogeneity and comparability when small numbers of hosts from a different demographic of the same species are included in samples. A mixed sample of sunfishes (Lepomis spp.) was subdivided in different ways and examined using cumulative performance curves to determine whether the exclusion of larger hosts from a single-species sample and/or the inclusion of hosts of the same size demographic from closely related host species would produce more homogeneous samples. The exclusion of larger hosts from the single-species samples tended to reduce the aggregation of the infrapopulation samples, and mixed-species samples of smaller fishes tended to have lower degrees of aggregation for a given sample size relative to the single-species sample. Cumulative performance curves for diversity and richness, in concert with nonmetric multidimensional scaling of the infracommunities, demonstrated sunfish size to be a more reliable determinant of infracommunity similarity than sunfish species in this particular sample. The results demonstrate that cumulative aggregation curves can be an effective tool for delineating homogeneous and comparable subsamples and that, under some circumstances, it is possible to offset the smaller sample sizes that result from the exclusion of older/larger hosts by the addition of congeneric or confamilial hosts within the same size/age classes as the stratified sample.

Effects of Hydrological Regime on Foliar Decomposition and Nutrient Release in the Riparian Zone of the Three Gorges Reservoir, China.

Foliar decomposition has significant effects on nutrient cycling and the productivity of riparian ecosystems, but studies on the impact of related hydrological dynamics have been lacking. Here, the litterbag method was carried out to compare decomposition and nutrient release characteristics in situ, including three foliage types [two single-species treatments using Taxodium distichum (L.) Rich., Salix matsudana Koidz., or a mixture with equal proportions of leaf mass], three flooding depths (unflooded, shallow flooding, and deep flooding), two hydrodynamic processes (continuous flooding and flooded-to-unflooded hydrological processes), and one hydrological cycle (1 year) in the riparian zone of the Three Gorges Reservoir. The results showed that both hydrological processes significantly promoted foliage decomposition, and all foliage types decomposed the fastest in a shallow flooding environment (P < 0.05). The mixed-species samples decomposed most quickly in the flooded hydrological process in the first half of the year and the unflooded hydrological process in the second half of the year. Flooding also significantly promoted the release of nutrients (P < 0.05). Mixed-species samples had the fastest release rates of carbon and nutrients in the flooded hydrological process in the first half of the year and the unflooded hydrological process in the second half of the year. Foliage decomposition was also closely related to environmental factors, such as water depth, temperature, and hydrological processes. Our research clarified the material cycling and energy flow process of the riparian ecosystem in the Three Gorges Reservoir area. It also provided a new reference for further understanding of foliage decomposition and nutrient release under different hydrological environments.

Correlation between the carbon isotopic composition of planktonic foraminifera-bound organic matter and surface water pCO2 across the equatorial Pacific

For times prior to those represented by the air trapped in Antarctic ice core records, the concentration of CO2 in the atmosphere must be reconstructed using geochemical proxies. The δ13C of particulate organic carbon (POC) produced in ocean surface waters has previously been observed to covary with the concentration of CO2 in the water. Relative to bulk sedimentary organic carbon, the minute quantity of organic matter trapped within the shell walls of planktonic foraminifera, “foraminifera-bound organic matter” (FBOM), has the potential advantage of being protected from diagenetic alteration and contamination by allochthonous organic matter. Here, with new protocols and instrumentation, FBOM-δ13C is investigated as a potential proxy for the aqueous CO2 concentration ([CO2(aq)]) and thus the partial pressure of CO2 (pCO2) in past surface waters. We achieve a full method precision for FBOM-δ13C of 0.4‰ (1SD) on sample sizes of 20 nanomole C by adding a cryofocus step, a helium sheath flow to the oxidation and reduction reactors, and other modifications to an elemental analyzer and by introducing new approaches to reduce contamination during sample preparation. FBOM-δ13C was analyzed in core-top sediments from the eastern tropical Pacific that span the equatorial maximum in surface water [CO2(aq)]. FBOM-δ13C is lower than predicted for marine phytoplankton, consistent with a substantial lipid component in FBOM. Anticorrelation is observed between FBOM-δ13C and climatological [CO2(aq)]; the relationship is statistically significant (P <0.05) in mixed-species samples and in 4 out of 5 picked species. The slope of the FBOM-δ13C:[CO2(aq)] anticorrelation is equivalent to or greater than has been measured for the δ13C of suspended POC in the surface ocean. Based on the few species analyzed in this study, endosymbiont-bearing and -barren species do not clearly differ from each other either in terms of their average value of FBOM-δ13C or the strength of the FBOM-δ13C:[CO2(aq)] anticorrelation, despite the recognized importance of the photosynthetic endosymbionts as a source of organic carbon for the symbiotic species. Correcting for variations in the δ13C of CO2(aq) and phytoplankton growth rate did not improve the significance of the FBOM-δ13C:[CO2(aq)] anticorrelation. The findings support the possibility that FBOM-δ13C can be used as a paleoceanographic proxy for surface water [CO2(aq)] and thus atmospheric pCO2.

Malaria Surveillance - United States, 2017.

Malaria Surveillance - United States, 2017.

Rapid direct detection of pathogens for diagnosis of joint infections by MALDI-TOF MS after liquid enrichment in the BacT/Alert blood culture system.

Pathogen identification is a critical step during diagnosis of infectious diseases. Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight mass spectrometry (MALDI-TOF-MS) has become the gold standard for identification of microorganisms cultured on solid media in microbiology laboratories. Direct identification of microbes from liquid specimen, circumventing the need for the additional overnight cultivation step, has been successfully established for blood culture, urine and liquor. Here, we evaluate the ability of MALDI-TOF MS for direct identification of pathogens in synovial fluid after liquid enrichment in BacT/Alert blood culture bottles. Influence of synovial specimen quality on direct species identification with the MALDI BioTyper/Sepsityper was tested with samples inoculated from pretested native synovia with concomitant inoculation of blood or pus, or highly viscous fluid. Here, we achieved >90% concordance with culture on solid medium, and only mixed-species samples posed significant problems. Performance in routine diagnostics was tested prospectively on bottles inoculated by treating physicians on ward. There, we achieved >70% concordance with culture on solid media. The major contributors to test failure were the absence of a measurable mass signal and mixed-specimen samples. The Sepsityper workflow worked well on samples derived from BacT/Alert blood culture bottles inoculated with synovial fluid, giving concordant results to identification from solid media. Host remnant material in the inoculum, such as blood or pus, had no detrimental effect on identification score values of the BioTyper system after processing with the Sepsityper workflow, and neither had the initial viscosity of the synovial sample.

Progress in the use of DNA barcodes in the identification and classification of medicinal plants

DNA barcoding is an emerging molecular identification and classification technology that has been applied to medicinal plants since 2008. The application of this technique has greatly ensured the safety and effectiveness of medicinal materials. In this paper, we review the application of DNA barcoding and some related technologies over the past 10 years with respect to improving our knowledge of medicinal plant identification and authentication. From single locus-based DNA barcodes to combined markers to genome-scale levels, DNA barcodes contribute more and more genetic information. At the same time, other technologies, such as high-resolution melting (HRM), have been combined with DNA barcoding. With the development of next-generation sequencing (NGS), metabarcoding technology has also been shown to identify species in mixed samples successfully. As a widely used and effective tool, DNA barcoding will become more useful over time in the field of medicinal plants.

Structural Changes in Boreal Forests Can Be Quantified Using Terrestrial Laser Scanning

Terrestrial laser scanning (TLS) has been adopted as a feasible technique to digitize trees and forest stands, providing accurate information on tree and forest structural attributes. However, there is limited understanding on how a variety of forest structural changes can be quantified using TLS in boreal forest conditions. In this study, we assessed the accuracy and feasibility of TLS in quantifying changes in the structure of boreal forests. We collected TLS data and field reference from 37 sample plots in 2014 (T1) and 2019 (T2). Tree stems typically have planar, vertical, and cylindrical characteristics in a point cloud, and thus we applied surface normal filtering, point cloud clustering, and RANSAC-cylinder filtering to identify these geometries and to characterize trees and forest stands at both time points. The results strengthened the existing knowledge that TLS has the capacity to characterize trees and forest stands in space and showed that TLS could characterize structural changes in time in boreal forest conditions. Root-mean-square-errors (RMSEs) in the estimates for changes in the tree attributes were 0.99–1.22 cm for diameter at breast height (Δdbh), 44.14–55.49 cm2 for basal area (Δg), and 1.91–4.85 m for tree height (Δh). In general, tree attributes were estimated more accurately for Scots pine trees, followed by Norway spruce and broadleaved trees. At the forest stand level, an RMSE of 0.60–1.13 cm was recorded for changes in basal area-weighted mean diameter (ΔDg), 0.81–2.26 m for changes in basal area-weighted mean height (ΔHg), 1.40–2.34 m2/ha for changes in mean basal area (ΔG), and 74–193 n/ha for changes in the number of trees per hectare (ΔTPH). The plot-level accuracy was higher in Scots pine-dominated sample plots than in Norway spruce-dominated and mixed-species sample plots. TLS-derived tree and forest structural attributes at time points T1 and T2 differed significantly from each other (p &lt; 0.05). If there was an increase or decrease in dbh, g, h, height of the crown base, crown ratio, Dg, Hg, or G recorded in the field, a similar outcome was achieved by using TLS. Our results provided new information on the feasibility of TLS for the purposes of forest ecosystem growth monitoring.

MinION sequencing of seafood in Singapore reveals creatively labelled flatfishes, confused roe, pig DNA in squid balls, and phantom crustaceans

Food mislabelling is a growing world-wide problem that can be addressed through the authentication of ingredients via techniques like mass spectrometry or DNA sequencing. However, unfortunately traditional DNA sequencing methods are slow, expensive, and require well-equipped laboratories. We here test whether these problems can be overcome through the use of Nanopore sequencing. We sequenced 92 single and 13 mixed-species samples purchased in Singapore. We successfully obtained DNA barcodes for 94% and 100% of the single- and mixed-species samples respectively by applying a bioinformatics pipeline that was optimised for this purpose. We find comparatively low levels of clear-cut mislabelling for single-species samples (7.6%), while the rates are higher for mixed-species samples (38.5%). The low rates for single-species samples are somewhat deceptive, however, because of the use of vague species names. With regard to the clearly mislabelled single-species products, higher-value products (e.g., prawn roe, wild-caught Atlantic salmon, halibut) are replaced with lower-value ingredients (e.g., fish roe, Pacific salmon, arrowtooth flounder) while more serious problems are observed for mixed-species samples. Cuttlefish and prawn balls repeatedly contained pig DNA and all but one of the mixed samples labelled as containing crustaceans (‘crab’, ‘prawn’, ‘lobster’) lacked a significant number of crustacean signals. We conclude that there is a need for more regular testing of seafood samples and suggest that due to speed and low-cost, MinION would be a good instrument for this purpose. We also emphasize the need for developing clearer labelling guidelines.

Evaluation and application of mitochondrial CO І gene in identification of endangered wildlife in multi-species mixed biological samples

In this study, the second-generation high-throughput sequencing and DNA barcoding were combined to manually prepare multi-species mixed samples, and the mitochondrial gene CO І was used as a barcode to simultaneously identify the animal species in the mixed samples and identify endangered species. The results showed that under the family and genus level, the simultaneous detection rate of the species in the mixed samples was as high as 100%, and the species identification rate was as high as 89% at the species level, and with high sensitivity, as little as 1% of the trace species could be detected. However, nearly 30% of non-target classification annotations appeared at the species level. It can be concluded that the mini CO I barcoding can be applied to the simultaneous identification of animal species in mixed biological samples, and the species identification rate is high. Non-target classification match existing at the species level can be further improved by increasing the length of the barcoding, improving the sequencing technology, reference database and so on. In this study, DNA metabarcoding technology was used to evaluate the feasibility of identification of endangered animals in multi-species mixed biological samples with CO І, in order to lay a preliminary foundation for the advancement of DNA metabarcoding method in the field of wildlife forensic identification.

Root distribution in intercropping systems – a comparison of DNA based methods and visual distinction of roots

ABSTRACT This study was performed to i) compare root distribution of legume/non-legume intercrops determined by qPCR and amplicon sequencing (Meta-barcoding) to root growth of the individual species determined visually, and ii) compare the qPCR and amplicon sequencing techniques as a method for quantifying root growth of individual species grown in mixtures. Red beet (Beta vulgaris L. cv Detroit) and lucerne (Medicago sativa L. cv Creno) were grown in one-meter-high transparent tubes. Root competition was studied by direct observation on the tube surface determining root intensity (RI), root wash and extraction followed by determination of root length density (RLD), and DNA-based methods. Intercropping decreased lucerne RI strongly, whereas the RI of red beet was not affected. The determination of RLD did not allow us to distinguish species in mixed samples. However, both DNA methods showed apparently a tendency to overestimate the fraction of lucerne roots compared to the direct root observations. The discrepancy between methods was explained by the fact that visual methods provide estimates of root length while the DNA methods provide estimates of root mass. In conclusion, DNA-based estimates of species fractions in mixed root samples give valuable information on root interactions in mixed crops.

Malaria Surveillance - United States, 2016.

Malaria Surveillance - United States, 2016.

CAFU: a Galaxy framework for exploring unmapped RNA-Seq data.

A widely used approach in transcriptome analysis is the alignment of short reads to a reference genome. However, owing to the deficiencies of specially designed analytical systems, short reads unmapped to the genome sequence are usually ignored, resulting in the loss of significant biological information and insights. To fill this gap, we present Comprehensive Assembly and Functional annotation of Unmapped RNA-Seq data (CAFU), a Galaxy-based framework that can facilitate the large-scale analysis of unmapped RNA sequencing (RNA-Seq) reads from single- and mixed-species samples. By taking advantage of machine learning techniques, CAFU addresses the issue of accurately identifying the species origin of transcripts assembled using unmapped reads from mixed-species samples. CAFU also represents an innovation in that it provides a comprehensive collection of functions required for transcript confidence evaluation, coding potential calculation, sequence and expression characterization and function annotation. These functions and their dependencies have been integrated into a Galaxy framework that provides access to CAFU via a user-friendly interface, dramatically simplifying complex exploration tasks involving unmapped RNA-Seq reads. CAFU has been validated with RNA-Seq data sets from wheat and Zea mays (maize) samples. CAFU is freely available via GitHub: https://github.com/cma2015/CAFU.

Proof-of-concept study of a new LC-ESI-MS/MS-based assay to identify Aspergillus spp. in artificially mixed samples using species/genus-specific proteotypic peptides

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) identification of microorganisms has shown its usefulness in clinical laboratories, but there are some important limitations associated with this technique. In this study, we present proof of concept of a newly developed assay which can resolve most of these MALDI-TOF MS limitations. This assay is based upon multiplex liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) for the targeted identification of different species in mixed samples. Four clinically relevant species of the fungal genus Aspergillus were used in this proof-of-concept study, and mixed samples were artificially prepared with strains of verified identity. The principle of the LC-ESI-MS/MS assay was based upon the detection of targeted Aspergillus species/genus-specific proteotypic peptide markers. Both pure material (i.e., single strains) and artificially mixed Aspergillus samples (with up to four constituents) were tested. Thirty selected Aspergillus species/genus-specific proteotypic peptides were applied in our LC-ESI-MS/MS assay after optimization. An overall success rate of 85 and 92.3% correct identification was obtained when testing the pure material and the artificially mixed Aspergillus samples, respectively. In contrast to MALDI-TOF MS, only one of the constituents of the artificially mixed Aspergillus sample could be correctly identified, whereas a nearly 100% success rate was obtained when testing the pure material. In conclusion, we have developed an innovative LC-ESI-MS/MS assay which has the capacity to determine the composition of mixed samples, and its proof of concept is shown here for Aspergillus species. This LC-ESI-MS/MS assay breaks new ground as a rapid and reliable tool for the identification of fungi and other microorganisms in clinical laboratories, even when dealing with samples in which the presence of multiple species is suspected.

Non-invasive bat species identification from mixed-species samples using a microarray

Identifying species from non-invasively collected, mixed species samples for biodiversity monitoring can be difficult and expensive using typical molecular methods because samples are often degraded. This is the case when identifying the species of bats present in roosts where guano may be the only means of assessment without disturbing the bats themselves. To aid in such studies, we developed species-specific DNA probes and a microarray capable of identifying most bat species in the United States and Canada using our existing database of 16S mitochondrial DNA sequences. The microarray was sensitive enough to detect DNA diluted 1:500 for several species combinations and was able to detect the presence of more species in mixed guano samples collected from roosts than did direct sequencing from individual fecal pellets. We suggest that these DNA probes and the microarray could be a valuable tool with which to non-invasively monitor bat populations and roost use.

Streaming algorithms for identification of pathogens and antibiotic resistance potential from real-time MinION(TM) sequencing.

The recently introduced Oxford Nanopore MinION platform generates DNA sequence data in real-time. This has great potential to shorten the sample-to-results time and is likely to have benefits such as rapid diagnosis of bacterial infection and identification of drug resistance. However, there are few tools available for streaming analysis of real-time sequencing data. Here, we present a framework for streaming analysis of MinION real-time sequence data, together with probabilistic streaming algorithms for species typing, strain typing and antibiotic resistance profile identification. Using four culture isolate samples, as well as a mixed-species sample, we demonstrate that bacterial species and strain information can be obtained within 30 min of sequencing and using about 500 reads, initial drug-resistance profiles within two hours, and complete resistance profiles within 10 h. While strain identification with multi-locus sequence typing required more than 15x coverage to generate confident assignments, our novel gene-presence typing could detect the presence of a known strain with 0.5x coverage. We also show that our pipeline can process over 100 times more data than the current throughput of the MinION on a desktop computer.Electronic supplementary materialThe online version of this article (doi:10.1186/s13742-016-0137-2) contains supplementary material, which is available to authorized users.