Development of a Lab-on-a-Chip Device for Rapid Nanotoxicity Assessment In Vitro

Increasing useof nanomaterials in consumer products and biomedical applications creates the possibilities of intentional/unintentional exposure to humans and the environment. Beyond the physiological limit, the nanomaterialexposure to humans can induce toxicity. It is difficult to define toxicity of nanoparticles on humans as it varies by nanomaterialcomposition, size, surface properties and the target organ/cell line. Traditional tests for nanomaterialtoxicity assessment are mostly based on bulk-colorimetric assays. In many studies, nanomaterials have found to interfere with assay-dye to produce false results and usually require several hours or days to collect results. Therefore, there is a clear need for alternative tools that can provide accurate, rapid, and sensitive measure of initial nanomaterialscreening. Recent advancement in single cell studies has suggested discovering cell properties not found earlier in traditional bulk assays. A complex phenomenon, like nanotoxicity, may become clearer when studied at the single cell level, including with small colonies of cells. Advances in lab-on-a-chip techniques have played a significant role in drug discoveries and biosensor applications, however, rarely explored for nanomaterialtoxicity assessment. We presented such cell-integrated chip-based approach that provided quantitative and rapid response of cellhealth, through electrochemical measurements. Moreover, the novel design of the device presented in this study was capable of capturing and analyzing the cells at a single cell and small cell-population level. We examined the change in exocytosis (i.e. neurotransmitterrelease) properties of a single PC12 cell, when exposed to CuOand TiO2 nanoparticles. We found both nanomaterials to interfere with the cell exocytosis function. We also studied the whole-cell response of a single-cell and a small cell-population simultaneously in real-time for the first time. The presented study can be a reference to the future research in the direction of nanotoxicity assessment to develop miniature, simple, and cost-effective tool for fast, quantitative measurements at high throughput level. The designed lab-on-a-chip device and measurement techniques utilized in the present work can be applied for the assessment of othernanoparticles' toxicity, as well.

Coastal plankton communities under elevated CO2: community barcoding results, link to data files in FASTA format

The acidification of the oceans could potentially alter marine plankton communities with consequences for ecosystem functioning. While several studies have investigated effects of ocean acidifications on communities using traditional methods, few have used genetic analyses. Here, we use community barcoding to assess the impact of ocean acidification on the composition of a coastal plankton community in a large scale, in situ, long-term mesocosm experiment. High-throughput sequencing resulted in the identification of a wide range of planktonic taxa (Alveolata, Cryptophyta, Haptophyceae, Fungi, Metazoa, Hydrozoa, Rhizaria, Straminipila, Chlorophyta). Analyses based on predicted operational taxonomical units as well as taxonomical compositions revealed no differences between communities in high CO2 mesocosms (~760 µatm) and those exposed to present day CO2 conditions. Observed shifts in the planktonic community composition were mainly related to seasonal changes in temperature and nutrients.

Fragilariopsis kerguelensis images from sediment core PS1768-8

Background: Light microscopic analysis of diatom frustules is widely used both in basic and applied research, notably taxonomy, morphometrics, water quality monitoring and paleo-environmental studies. In these applications, usually large numbers of frustules need to be identified and / or measured. Although there is a need for automation in these applications, and image processing and analysis methods supporting these tasks have previously been developed, they did not become widespread in diatom analysis. While methodological reports for a wide variety of methods for image segmentation, diatom identification and feature extraction are available, no single implementation combining a subset of these into a readily applicable workflow accessible to diatomists exists. Results: The newly developed tool SHERPA offers a versatile image processing workflow focused on the identification and measurement of object outlines, handling all steps from image segmentation over object identification to feature extraction, and providing interactive functions for reviewing and revising results. Special attention was given to ease of use, applicability to a broad range of data and problems, and supporting high throughput analyses with minimal manual intervention. Conclusions: Tested with several diatom datasets from different sources and of various compositions, SHERPA proved its ability to successfully analyze large amounts of diatom micrographs depicting a broad range of species. SHERPA is unique in combining the following features: application of multiple segmentation methods and selection of the one giving the best result for each individual object; identification of shapes of interest based on outline matching against a template library; quality scoring and ranking of resulting outlines supporting quick quality checking; extraction of a wide range of outline shape descriptors widely used in diatom studies and elsewhere; minimizing the need for, but enabling manual quality control and corrections. Although primarily developed for analyzing images of diatom valves originating from automated microscopy, SHERPA can also be useful for other object detection, segmentation and outline-based identification problems.

Isolation and Characterization of Microsatellite DNA Markers in the Deep-Sea Amphipod Paralicella tenuipes by Illumina MiSeq Sequencing

Funding This work was supported by the HADEEP projects, funded by the Nippon Foundation, Japan (2009765188), the Natural Environmental Research Council, UK (NE/E007171/1) and the Total Foundation, France. We acknowledge additional support from the Marine Alliance for Science and Technology for Scotland (MASTS) funded by the Scottish Funding Council (Ref: HR09011) and contributing institutions. We also acknowledge support from the Leverhulme Trust to SBP. Additional sea time was supported by NIWA’s ‘Impact of Resource Use on Vulnerable Deep-Sea Communities’ project (CO1_0906)

Genome-wide association of multiple complex traits in outbred mice by ultra low-coverage sequencing

We thank the High-Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics and the Wellcome Trust Sanger Institute for the generation of the sequencing data. This work was funded by Wellcome Trust grant 090532/Z/09/Z (J.F.). Primary phenotyping of the mice was supported by the Mary Lyon Centre and Mammalian Genetics Unit (Medical Research Council, UK Hub grant G0900747 91070 and Medical Research Council, UK grant MC U142684172). D.A.B acknowledges support from NIH R01AR056280. The sleep work was supported by the state of Vaud (Switzerland) and the Swiss National Science Foundation (SNF 14694 and 136201 to P.F.). The ECG work was supported by the Netherlands CardioVascular Research Initiative (Dutch Heart Foundation, Dutch Federation of University Medical Centres, the Netherlands Organization for Health Research and Development, and the Royal Netherlands Academy of Sciences) PREDICT project, InterUniversity Cardiology Institute of the Netherlands (ICIN; 061.02; C.A.R., C.R.B). Na Cai is supported by the Agency of Science, Technology and Research (A*STAR) Graduate Academy. The authors wish to acknowledge excellent technical assistance from: Ayako Kurioka, Leo Swadling, Catherine de Lara, James Ussher, Rachel Townsend, Sima Lionikaite, Ausra S. Lionikiene, Rianne Wolswinkel and Inge van der Made. We would like to thank Thomas M Keane and Anthony G Doran for their help in annotating variants and adding the FVB/NJ strain to the Mouse Genomes Project.

Dissecting the Functional Impacts of Non-Coding Genetic Variation

A large proportion of the variation in traits between individuals can be attributed to variation in the nucleotide sequence of the genome. The most commonly studied traits in human genetics are related to disease and disease susceptibility. Although scientists have identified genetic causes for over 4,000 monogenic diseases, the underlying mechanisms of many highly prevalent multifactorial inheritance disorders such as diabetes, obesity, and cardiovascular disease remain largely unknown. Identifying genetic mechanisms for complex traits has been challenging because most of the variants are located outside of protein-coding regions, and determining the effects of such non-coding variants remains difficult. In this dissertation, I evaluate the hypothesis that such non-coding variants contribute to human traits and diseases by altering the regulation of genes rather than the sequence of those genes. I will specifically focus on studies to determine the functional impacts of genetic variation associated with two related complex traits: gestational hyperglycemia and fetal adiposity. At the genomic locus associated with maternal hyperglycemia, we found that genetic variation in regulatory elements altered the expression of the HKDC1 gene. Furthermore, we demonstrated that HKDC1 phosphorylates glucose in vitro and in vivo, thus demonstrating that HKDC1 is a fifth human hexokinase gene. At the fetal-adiposity associated locus, we identified variants that likely alter VEPH1 expression in preadipocytes during differentiation. To make such studies of regulatory variation high-throughput and routine, we developed POP-STARR, a novel high throughput reporter assay that can empirically measure the effects of regulatory variants directly from patient DNA. By combining targeted genome capture technologies with STARR-seq, we assayed thousands of haplotypes from 760 individuals in a single experiment. We subsequently used POP-STARR to identify three key features of regulatory variants: that regulatory variants typically have weak effects on gene expression; that the effects of regulatory variants are often coordinated with respect to disease-risk, suggesting a general mechanism by which the weak effects can together have phenotypic impact; and that nucleotide transversions have larger impacts on enhancer activity than transitions. Together, the findings presented here demonstrate successful strategies for determining the regulatory mechanisms underlying genetic associations with human traits and diseases, and value of doing so for driving novel biological discovery.

New Advancements of Scalable Statistical Methods for Learning Latent Structures in Big Data

Constant technology advances have caused data explosion in recent years. Accord- ingly modern statistical and machine learning methods must be adapted to deal with complex and heterogeneous data types. This phenomenon is particularly true for an- alyzing biological data. For example DNA sequence data can be viewed as categorical variables with each nucleotide taking four different categories. The gene expression data, depending on the quantitative technology, could be continuous numbers or counts. With the advancement of high-throughput technology, the abundance of such data becomes unprecedentedly rich. Therefore efficient statistical approaches are crucial in this big data era.

Previous statistical methods for big data often aim to find low dimensional struc- tures in the observed data. For example in a factor analysis model a latent Gaussian distributed multivariate vector is assumed. With this assumption a factor model produces a low rank estimation of the covariance of the observed variables. Another example is the latent Dirichlet allocation model for documents. The mixture pro- portions of topics, represented by a Dirichlet distributed variable, is assumed. This dissertation proposes several novel extensions to the previous statistical methods that are developed to address challenges in big data. Those novel methods are applied in multiple real world applications including construction of condition specific gene co-expression networks, estimating shared topics among newsgroups, analysis of pro- moter sequences, analysis of political-economics risk data and estimating population structure from genotype data.

Acoustic and Magnetic Techniques for the Isolation and Analysis of Cells in Microfluidic Platforms

Cancer comprises a collection of diseases, all of which begin with abnormal tissue growth from various stimuli, including (but not limited to): heredity, genetic mutation, exposure to harmful substances, radiation as well as poor dieting and lack of exercise. The early detection of cancer is vital to providing life-saving, therapeutic intervention. However, current methods for detection (e.g., tissue biopsy, endoscopy and medical imaging) often suffer from low patient compliance and an elevated risk of complications in elderly patients. As such, many are looking to “liquid biopsies” for clues into presence and status of cancer due to its minimal invasiveness and ability to provide rich information about the native tumor. In such liquid biopsies, peripheral blood is drawn from patients and is screened for key biomarkers, chiefly circulating tumor cells (CTCs). Capturing, enumerating and analyzing the genetic and metabolomic characteristics of these CTCs may hold the key for guiding doctors to better understand the source of cancer at an earlier stage for more efficacious disease management.

The isolation of CTCs from whole blood, however, remains a significant challenge due to their (i) low abundance, (ii) lack of a universal surface marker and (iii) epithelial-mesenchymal transition that down-regulates common surface markers (e.g., EpCAM), reducing their likelihood of detection via positive selection assays. These factors potentiate the need for an improved cell isolation strategy that can collect CTCs via both positive and negative selection modalities as to avoid the reliance on a single marker, or set of markers, for more accurate enumeration and diagnosis.

The technologies proposed herein offer a unique set of strategies to focus, sort and template cells in three independent microfluidic modules. The first module exploits ultrasonic standing waves and a class of elastomeric particles for the rapid and discriminate sequestration of cells. This type of cell handling holds promise not only in sorting, but also in the isolation of soluble markers from biofluids. The second module contains components to focus (i.e., arrange) cells via forces from acoustic standing waves and separate cells in a high throughput fashion via free-flow magnetophoresis. The third module uses a printed array of micromagnets to capture magnetically labeled cells into well-defined compartments, enabling on-chip staining and single cell analysis. These technologies can operate in standalone formats, or can be adapted to operate with established analytical technologies, such as flow cytometry. A key advantage of these innovations is their ability to process erythrocyte-lysed blood in a rapid (and thus high throughput) fashion. They can process fluids at a variety of concentrations and flow rates, target cells with various immunophenotypes and sort cells via positive (and potentially negative) selection. These technologies are chip-based, fabricated using standard clean room equipment, towards a disposable clinical tool. With further optimization in design and performance, these technologies might aid in the early detection, and potentially treatment, of cancer and various other physical ailments.

The Roles of Phenotypic Plasticity and Plant-Microbe Interactions in the Evolution of Complex Traits in Boechera stricta

All organisms live in complex habitats that shape the course of their evolution by altering the phenotype expressed by a given genotype (a phenomenon known as phenotypic plasticity) and simultaneously by determining the evolutionary fitness of that phenotype. In some cases, phenotypic evolution may alter the environment experienced by future generations. This dissertation describes how genetic and environmental variation act synergistically to affect the evolution of glucosinolate defensive chemistry and flowering time in Boechera stricta, a wild perennial herb. I focus particularly on plant-associated microbes as a part of the plant’s environment that may alter trait evolution and in turn be affected by the evolution of those traits. In the first chapter I measure glucosinolate production and reproductive fitness of over 1,500 plants grown in common gardens in four diverse natural habitats, to describe how patterns of plasticity and natural selection intersect and may influence glucosinolate evolution. I detected extensive genetic variation for glucosinolate plasticity and determined that plasticity may aid colonization of new habitats by moving phenotypes in the same direction as natural selection. In the second chapter I conduct a greenhouse experiment to test whether naturally-occurring soil microbial communities contributed to the differences in phenotype and selection that I observed in the field experiment. I found that soil microbes cause plasticity of flowering time but not glucosinolate production, and that they may contribute to natural selection on both traits; thus, non-pathogenic plant-associated microbes are an environmental feature that could shape plant evolution. In the third chapter, I combine a multi-year, multi-habitat field experiment with high-throughput amplicon sequencing to determine whether B. stricta-associated microbial communities are shaped by plant genetic variation. I found that plant genotype predicts the diversity and composition of leaf-dwelling bacterial communities, but not root-associated bacterial communities. Furthermore, patterns of host genetic control over associated bacteria were largely site-dependent, indicating an important role for genotype-by-environment interactions in microbiome assembly. Together, my results suggest that soil microbes influence the evolution of plant functional traits and, because they are sensitive to plant genetic variation, this trait evolution may alter the microbial neighborhood of future B. stricta generations. Complex patterns of plasticity, selection, and symbiosis in natural habitats may impact the evolution of glucosinolate profiles in Boechera stricta.

Sequence and Structural Determinants of Specificity Differences between Paralogous Transcription Factors

Transcription factors (TFs) control the temporal and spatial expression of target genes by interacting with DNA in a sequence-specific manner. Recent advances in high throughput experiments that measure TF-DNA interactions in vitro and in vivo have facilitated the identification of DNA binding sites for thousands of TFs. However, it remains unclear how each individual TF achieves its specificity, especially in the case of paralogous TFs that recognize distinct target genomic sites despite sharing very similar DNA binding motifs. In my work, I used a combination of high throughput in vitro protein-DNA binding assays and machine-learning algorithms to characterize and model the binding specificity of 11 paralogous TFs from 4 distinct structural families. My work proves that even very closely related paralogous TFs, with indistinguishable DNA binding motifs, oftentimes exhibit differential binding specificity for their genomic target sites, especially for sites with moderate binding affinity. Importantly, the differences I identify in vitro and through computational modeling help explain, at least in part, the differential in vivo genomic targeting by paralogous TFs. Future work will focus on in vivo factors that might also be important for specificity differences between paralogous TFs, such as DNA methylation, interactions with protein cofactors, or the chromatin environment. In this larger context, my work emphasizes the importance of intrinsic DNA binding specificity in targeting of paralogous TFs to the genome.

Cell Fate Specification and the Regulation of RNA-dependent DNA Methylation in the Arabidopsis Root Meristem

The Arabidopsis root apical meristem (RAM) is a complex tissue capable of generating all the cell types that ultimately make up the root. The work presented in this thesis takes advantage of the versatility of high-throughput sequencing to address two independent questions about the root meristem. Although a lot of information is known regarding the cell fate decisions that occur at the RAM, cortex specification and differentiation remain poorly understood. In the first part of this thesis, I used an ethylmethanesulfonate (EMS) mutagenized marker line to perform a forward genetics screen. The goal of this screen was to identify novel genes involved in the specification and differentiation of the cortex tissue. Mapping analysis from the results obtained in this screen revealed a new allele of BRASSINOSTEROID4 with abnormal marker expression in the cortex tissue. Although this allele proved to be non-cortex specific, this project highlights new technology that allows mapping of EMS-generated mutations without the need to map-cross or back-cross. In the second part of this thesis, using fluorescence activated cell sorting (FACS) coupled with high throughput sequencing, my collaborators and I generated single-base resolution whole genome DNA methylomes, mRNA transcriptomes, and smallRNA transcriptomes for six different populations of cell types in the Arabidopsis root meristem. We were able to discover that the columella is hypermethylated in the CHH context within transposable elements. This hypermethylation is accompanied by upregulation of the RNA-dependent DNA methylation pathway (RdDM), including higher levels of 24-nt silencing RNAs (siRNAs). In summary, our studies demonstrate the versatility of high-throughput sequencing as a method for identifying single mutations or to perform complex comparative genomic analyses.

microRNA Regulation of Cellular Immunity

Immunity is broadly defined as a mechanism of protection against non-self entities, a process which must be sufficiently robust to both eliminate the initial foreign body and then be maintained over the life of the host. Life-long immunity is impossible without the development of immunological memory, of which a central component is the cellular immune system, or T cells. Cellular immunity hinges upon a naïve T cell pool of sufficient size and breadth to enable Darwinian selection of clones responsive to foreign antigens during an initial encounter. Further, the generation and maintenance of memory T cells is required for rapid clearance responses against repeated insult, and so this small memory pool must be actively maintained by pro-survival cytokine signals over the life of the host.

T cell development, function, and maintenance are regulated on a number of molecular levels through complex regulatory networks. Recently, small non-coding RNAs, miRNAs, have been observed to have profound impacts on diverse aspects of T cell biology by impeding the translation of RNA transcripts to protein. While many miRNAs have been described that alter T cell development or functional differentiation, little is known regarding the role that miRNAs have in T cell maintenance in the periphery at homeostasis.

In Chapter 3 of this dissertation, tools to study miRNA biology and function were developed. First, to understand the effect that miRNA overexpression had on T cell responses, a novel overexpression system was developed to enhance the processing efficiency and ultimate expression of a given miRNA by placing it within an alternative miRNA backbone. Next, a conditional knockout mouse system was devised to specifically delete miR-191 in a cell population expressing recombinase. This strategy was expanded to permit the selective deletion of single miRNAs from within a cluster to discern the effects of specific miRNAs that were previously inaccessible in isolation. Last, to enable the identification of potentially therapeutically viable miRNA function and/or expression modulators, a high-throughput flow cytometry-based screening system utilizing miRNA activity reporters was tested and validated. Thus, several novel and useful tools were developed to assist in the studies described in Chapter 4 and in future miRNA studies.

In Chapter 4 of this dissertation, the role of miR-191 in T cell biology was evaluated. Using tools developed in Chapter 3, miR-191 was observed to be critical for T cell survival following activation-induced cell death, while proliferation was unaffected by alterations in miR-191 expression. Loss of miR-191 led to significant decreases in the numbers of CD4+ and CD8+ T cells in the periphery lymph nodes, but this loss had no impact on the homeostatic activation of either CD4+ or CD8+ cells. These peripheral changes were not caused by gross defects in thymic development, but rather impaired STAT5 phosphorylation downstream of pro-survival cytokine signals. miR-191 does not specifically inhibit STAT5, but rather directly targets the scaffolding protein, IRS1, which in turn alters cytokine-dependent signaling. The defect in peripheral T cell maintenance was exacerbated by the presence of a Bcl-2YFP transgene, which led to even greater peripheral T cell losses in addition to developmental defects. These studies collectively demonstrate that miR-191 controls peripheral T cell maintenance by modulating homeostatic cytokine signaling through the regulation of IRS1 expression and downstream STAT5 phosphorylation.

The studies described in this dissertation collectively demonstrate that miR-191 has a profound role in the maintenance of T cells at homeostasis in the periphery. Importantly, the manipulation of miR-191 altered immune homeostasis without leading to severe immunodeficiency or autoimmunity. As much data exists on the causative agents disrupting active immune responses and the formation of immunological memory, the basic processes underlying the continued maintenance of a functioning immune system must be fully characterized to facilitate the development of methods for promoting healthy immune function throughout the life of the individual. These findings also have powerful implications for the ability of patients with modest perturbations in T cell homeostasis to effectively fight disease and respond to vaccination and may provide valuable targets for therapeutic intervention.

The application of next generation sequencing to profile microbe related cheese quality defects

High throughput next generation sequencing, together with advanced molecular methods, has considerably enhanced the field of food microbiology. By overcoming biases associated with culture dependant approaches, it has become possible to achieve novel insights into the nature of food-borne microbial communities. In this thesis, several different sequencing-based approaches were applied with a view to better understanding microbe associated quality defects in cheese. Initially, a literature review provides an overview of microbe-associated cheese quality defects as well as molecular methods for profiling complex microbial communities. Following this, 16S rRNA sequencing revealed temporal and spatial differences in microbial composition due to the time during the production day that specific commercial cheeses were manufactured. A novel Ion PGM sequencing approach, focusing on decarboxylase genes rather than 16S rRNA genes, was then successfully employed to profile the biogenic amine producing cohort of a series of artisanal cheeses. Investigations into the phenomenon of cheese pinking formed the basis of a joint 16S rRNA and whole genome shotgun sequencing approach, leading to the identification of Thermus species and, more specifically, the pathway involved in production of lycopene, a red coloured carotenoid. Finally, using a more traditional approach, the effect of addition of a facultatively heterofermentative Lactobacillus (Lactobacillus casei) to a Swiss-type cheese, in which starter activity was compromised, was investigated from the perspective of its ability to promote gas defects and irregular eye formation. X-ray computed tomography was used to visualise, using a non-destructive method, the consequences of the undesirable gas formation that resulted. Ultimately this thesis has demonstrated that the application of molecular techniques, such as next generation sequencing, can provide a detailed insight into defect-causing microbial populations present and thereby may underpin approaches to optimise the quality and consistency of a wide variety of cheeses.

Interspecific competition between the potato cyst nematode species Globodera pallida and G. rostochiensis

The two potato cyst nematode species, Globodera pallida and G. rostochiensis, are among the most important pests of potato. PCN are difficult to manage, while the two species respond differently to the main control methods. An increase in the incidence of G. pallida had been reported and is generally attributed to greater effectiveness of control measures against G. rostochiensis. The status of PCN in Ireland was studied using PCR. The results demonstrated qPCR to be an efficient means of high-throughput PCN sampling, being able to accurately identify both species in mixed-species populations. Species discrimination using qPCR revealed an increase in the incidence of G. pallida in Ireland in the absence of G. pallida-selective control measures. The population dynamics of G. pallida and G. rostochiensis in Ireland were studied in mixed- and single-species competition assays in vivo. G. pallida proved to be the more successful species, with greater multiplication in mixed- than single-species populations, with G. rostochiensis showing the opposite. This effect was similarly observed in staggered inoculation trials and population proportion trials. It was hypothesised that the greater G. pallida competitiveness could be attributed to its later hatch. G. pallida exhibited a later peak in hatching activity and more prolonged hatch, relative to G. rostochiensis. G. rostochiensis hatch was significantly reduced in mixedspecies hatching assays. G. pallida hatch was significantly higher when hatch was induced in potato root leachates containing G. rostochiensis-specific compounds, indicating that G. pallida hatch is stimulated upon perception of G. rostochiensis–derived compounds. Rhizotron studies revealed that root damage, caused by feeding of the early-hatching G. rostochiensis, resulted in increased lateral root proliferation and significantly increased G. pallida multiplication. Split-root trials indicated a significant G. pallida-induced ISR effect. G. rostochiensis multiplication was significantly reduced in split-root rhizotrons when G. pallida colonised roots before or after G. rostochiensis infection.

Metabarcoding approach for non-indigenous species surveillance in marine coastal waters

In this study, high-throughput sequencing (HTS) metabarcoding was applied for the surveillance of plankton communities within the southeastern (SE) Baltic Sea coastal zone. These results were compared with those from routine monitoring survey and morphological analyses. Four of five nonindigenous species found in the samples were identified exclusively by metabarcoding. All of them are considered as invasive in the Baltic Sea with reported impact on the ecosystem and biodiversity. This study indicates that, despite some current limitations, HTS metabarcoding can provide information on the presence of exotic species and advantageously complement conventional approaches, only requiring the same monitoring effort as before. Even in the currently immature status of HTS, this combination of HTS metabarcoding and observational records is recommended in the early detection of marine pests and delivery of the environmental status metrics of nonindigenous species.