Direct classification of related species of fungal endophytes (Epichlo? spp.) using visible and near-infrared spectroscopy and multivariate analysis.

The aim of this work was to investigate the potential of visible and near-infrared (Vis-NIR) reflectance spectroscopy for the classification of three morphologically similar species of fungal endophytes of grasses. Vis-NIR spectra (400-2498 nm) from 34 isolates of Epichlo? sylvatica, 32 of Epichlo? typhina and 38 of Epichlo? festucae were recorded directly from fresh mycelium growing in potato dextrose agar plates. Multivariate procedures applied to the spectral data were discriminant modified partial least squares regression, soft independent modelling of class analogy and discriminant partial least squares regressions (PLS1, PLS2). Several types of data pretreatments were tested to develop the classification models. The best predictive models were achieved with PLS2 analysis; with this method, 90% of E. typhina and 100% of E. festucae and E. sylvatica external validation samples were successfully classified. These results show the potential of Vis-NIR spectroscopy combined with multivariate analysis as a rapid method for classifying morphologically similar species of filamentous fungi.     

Relationships between the genetic distance of Epichloë festucae isolates and the ergovaline and peramine contents of their Festuca rubra hosts

In semiarid grasslands of western Spain, plants of Festuca rubra are frequently infected by Epichloë festucae , an endophyte capable of producing the alkaloids ergovaline, toxic to mammals, and peramine, toxic to insects. The objectives of this paper were to estimate the variability in the content of ergovaline and peramine in plants of Festuca rubra from natural populations and to determine the relationship between the genetic distance among Epichloë strains and the alkaloid contents of plants infected by them. The results showed that a significant variation exits in the ergovaline and peramine contents of infected F. rubra plants, and that variation patterns are different for each alkaloid. Ergovaline content showed a significant variation between years. In contrast, most variation observed in the concentration of peramine occurred between populations. Mantel tests, constrained correspondence analysis (CCA) and generalised analysis of molecular variance (GAMOVA) all revealed a significant relationship between the genetic distances among 35 Epichloë isolates, and the differences in peramine content of their host plants. The relationship observed for ergovaline was more ambiguous. This indicates that plants infected by genetically close isolates of Epichloë festucae tend to be similar in terms of peramine content, while the ergovaline content of infected plants seems to be more dependent on external factors. The results of this study suggest that the selection of Epichloë festucae endophytes based on the alkaloid content of their host plants can be a successful strategy to select good or bad producers of peramine, but may not be a reliable method to detect fungal strains associated with particular ergovaline production profiles.     

The evolutionary origins of three new Neotyphodium endophyte species from grasses indigenous to the Southern Hemisphere

Members of the genus Neotyphodium are asexual, seedborne, protective fungal endophytes of cool season grasses that have likely evolved either directly from sexual Epichlo?; species, or by the interspecific hybridization of distinct lineages of Epichlo?; and Neotyphodium. We investigated the evolutionary origins of Neotyphodium endophytes from several grasses that are indigenous to the Southern Hemisphere using a multiple-gene phylogenetic approach. Intron regions of the genes encoding β-tubulin (tub2), translation elongation factor 1-α (tef1) and actin (act1) were amplified by polymerase chain reaction and sequenced. Phylogenetic analyses of these sequences, aligned with homologous sequences from Epichlo?; spp., revealed the evolutionary origins of the Southern Hemisphere endophytes, where one lineage of apparently non-hybrid origin, and three lineages of unique interspecific hybrid origin were identified. On the basis of morphology, host range and evolutionary history, we propose three new species of Neotyphodium. Neotyphodium aotearoae was isolated from Echinopogon ovatus populations from New Zealand and Australia, and comprised a unique, apparently non-hybrid lineage within the Epichlo?; species phylogeny. In contrast, an interspecific hybrid lineage was identified from two Australian Ec. ovatus populations, whose ancestry apparently involved lineages closely related to extant E. festucae and an E. typhina genotype similar to that of isolates from Poa pratensis. Endophytes infecting South African Melica racemosa and M. decumbens (dronkgras) appeared to be hybrids of E. festucae and N. aotearoae or close relatives. The names N. australiense and N. melicicola are proposed for these two hybrid lineages, respectively. The origin of N. tembladerae, an established endophyte species from South American Poa and Festuca spp., was also investigated. Neotyphodium tembladerae appeared to be of hybrid origin, involving E. festucae and an E. typhina genotype similar to that of isolates from Poa nemoralis. The results of this study highlight the widespread occurrence of interspecific hybrid Neotyphodium lineages on a global scale, and the extent of endophyte gene-flow between the Northern and Southern Hemispheres.     

Combining hyperspectral imaging and chemometrics to assess and interpret the effects of environmental stressors on zebrafish eye images at tissue level

Changes on an organism by the exposure to environmental stressors may be characterized by hyperspectral images (HSI), which preserve the morphology of biological samples, and suitable chemometric tools. The approach proposed allows assessing and interpreting the effect of contaminant exposure on heterogeneous biological samples monitored by HSI at specific tissue levels. In this work, the model example used consists of the study of the effect of the exposure of chlorpyrifos‐oxon on zebrafish tissues. To assess this effect, unmixing of the biological sample images followed by tissue‐specific classification models based on the unmixed spectral signatures is proposed. Unmixing and classification are performed by multivariate curve resolution‐alternating least squares (MCR‐ALS) and partial least squares‐discriminant analysis (PLS‐DA), respectively. Crucial aspects of the approach are: (1) the simultaneous MCR‐ALS analysis of all images from 1 population to take into account biological variability and provide reliable tissue spectral signatures, and (2) the use of resolved spectral signatures from control and exposed populations obtained from resampling of pixel subsets analyzed by MCR‐ALS multiset analysis as information for the tissue‐specific PLS‐DA classification models. Classification results diagnose the presence of a significant effect and identify the spectral regions at a tissue level responsible for the biological change.      

A test of host specialization by insect vectors as a mechanism for reproductive isolation among entomophilous fungal species

Epichloë species are self incompatible (heterothallic) fungi that must be fertilized by spermatia from individuals of opposite mating type for successful sexual reproduction to occur. Female flies of the genus Botanophila act as vectors of the fungi by ingesting and defecating spermatia (gametes) onto fungal stromata (fruiting bodies) after oviposition. Larvae feed and develop on the stromata and thus maintain a symbiotic relationship with Epichloë fungi. We hypothesized that sole dependence on fertilized stromata as a food source would promote specialization by flies to single compatible host species and that this specialization would promote reproductive isolation among Epichloë species. Analysis of progeny of ascospores from experimental field plots in Zurich, Switzerland, indicated prevalence of specific matings between stromata of the same host, and thus was consistent with the hypothesis that flies are species-specific in their visitation behaviour. Genetic analyses of spermatia contained in the faeces of individual flies also gave some support for this hypothesis. We recovered spermatia of 4 different Epichloë species from fly faeces. Comparison of spermatia found in fly faeces to those available from stromata showed flies avoided Epichloë clarkii and may have preferred Epichloë typhina . Interestingly, these are the only two Epichloë species known to be interfertile with one another. Individual flies tended to carry spermatia predominantly from one fungal species. Thus, flies may adopt a type of "majoring" and "minoring" behaviour when visiting fungi. Yet, Botanophila flies are not monolectic and often visited all hosts that were available within screened cages. In addition to any reproductive isolation flies may provide to some fungal species, differences in competitiveness among spermatia of different species deposited on the same stroma may favor intraspecific matings.     

Comparison of visible and near infrared reflectance spectroscopy on fat to authenticate dietary history of lambs

Since consumers are showing increased interest in the origin and method of production of their food, it is important to be able to authenticate dietary history of animals by rapid and robust methods used in the ruminant products. Promising breakthroughs have been made in the use of spectroscopic methods on fat to discriminate pasture-fed and concentrate-fed lambs. However, questions remained on their discriminatory ability in more complex feeding conditions, such as concentrate-finishing after pasture-feeding. We compared the ability of visible reflectance spectroscopy (Vis RS, wavelength range: 400 to 700 nm) with that of visible-near-infrared reflectance spectroscopy (Vis-NIR RS, wavelength range: 400 to 2500 nm) to differentiate between carcasses of lambs reared with three feeding regimes, using partial least square discriminant analysis (PLS-DA) as a classification method. The sample set comprised perirenal fat of Romane male lambs fattened at pasture (P, n=69), stall-fattened indoors on commercial concentrate and straw (S, n=55) and finished indoors with concentrate and straw for 28 days after pasture-feeding (PS, n=65). The overall correct classification rate was better for Vis-NIR RS than for Vis RS (99.0% v. 95.1%, P<0.05). Vis-NIR RS allowed a correct classification rate of 98.6%, 100.0% and 98.5% for P, S and PS lambs, respectively, whereas Vis RS allowed a correct classification rate of 98.6%, 94.5% and 92.3% for P, S and PS lambs, respectively. This study suggests the likely implication of molecules absorbing light in the non-visible part of the Vis-NIR spectra (possibly fatty acids), together with carotenoid and haem pigments, in the discrimination of the three feeding regimes.     

Using FTIR to predict saccharification from enzymatic hydrolysis of alkali-pretreated biomasses

Fourier transform infrared, attenuated total reflectance (FTIR-ATR) spectroscopy combined with partial least squares (PLS) regression accurately predicted 72-h glucose and xylose conversions (g sugars/100 g potential sugars) and yields (g sugars/100 g dry solids) from cellulase-mediated hydrolysis of alkali-pretreated lignocellulose. Six plant biomasses that represent a variety of potential biofuel feedstocks--two switchgrass cultivars, big bluestem grass, a low-impact, high-diversity mixture of 32 species of prairie biomasses, mixed hardwood, and corn stover--were subjected to four levels of low-temperature NaOH pretreatment to produce 24 samples with a wide range of potential digestibility. PLS models were constructed by correlating FTIR spectra of pretreated samples to measured values of gluose and xylose conversions and yields. Variable selection, based on 90% confidence intervals of regression-coefficient matrices, improved the predictive ability of the models, while simplifying them considerably. Final models predicted sugar conversions with coefficient of determination for cross-validation (Q(2)) values of 0.90 for glucose and 0.89 for xylose, and sugar yields with Q(2) values of 0.92 for glucose and 0.91 for xylose. The sugar-yield models are noteworthy for their ability to predict enzymatic saccharification per mass dry solids without a priori knowledge of the composition of the solids. All peaks retained in the final regression coefficient matrices were previously assigned to chemical bonds and functional groups in lignocellulose, demonstrating that the models were based on real chemical information. This study demonstrates that FTIR spectroscopy combined with PLS regression can be used to rapidly estimate sugar conversions and yields from enzymatic hydrolysis of pretreated plant biomass.     

Simultaneous Prediction of Human Antithrombin III and Main Metabolites in Animal Cell Culture Processes by Near-Infrared Spectroscopy

Samples of cell culture supernatants were analysed by near-infrared (NIR) spectroscopy. Spectral information was used to generate calibration models by using multivariate partial least squares (PLS) regression. Concentration predictions by these models were in good agreement with the values produced by conventional methods. Due to the simple pre-treatment of the sample and the short time required for measurement and prediction, NIR is a promising tool for automation of a cell culture process.     

Raman spectroscopy as a method to replace off-line pH during mammalian cell culture processes

Raman spectroscopy is a robust, well-established tool utilized for measuring important cell culture process variables for example, feed, metabolites, and biomass in real-time. This study further expands the functionality of in-line Raman spectroscopy coupled with partial least squares (PLS) regression modelling to develop a pH measurement tool. Cell line specific models were developed to enhance the robustness for processes with different pH setpoints, deadbands, and cellular metabolism. The modelling strategy further improved robustness by reducing the temporal complexity of pH shifts by splitting data sets into two time zones reflective of major changes in pH. In addition, models were developed to assess if lactate and partial pressure of carbon dioxide (pCO₂) could be used in a PLS model for pH. Splitting the data sets into early and late for the process resulted in errors of 0.035 pH and 0.034 pH for the two respective Raman cell lines models which was within acceptance criteria. The lactate and pCO₂ PLS model with values provided by Raman models had a further 0.001 pH error reduction. This study illustrates the potential to eliminate off-line samples to correct for in-line measurements of pH and further illustrates the capabilities of Raman to measure additional process variables.     

In situ Raman spectroscopy for simultaneous monitoring of multiple process parameters in mammalian cell culture bioreactors

In this study, the application of Raman spectroscopy to the simultaneous quantitative determination of glucose, glutamine, lactate, ammonia, glutamate, total cell density (TCD), and viable cell density (VCD) in a CHO fed‐batch process was demonstrated in situ in 3 L and 15 L bioreactors. Spectral preprocessing and partial least squares (PLS) regression were used to correlate spectral data with off‐line reference data. Separate PLS calibration models were developed for each analyte at the 3 L laboratory bioreactor scale before assessing its transferability to the same bioprocess conducted at the 15 L pilot scale. PLS calibration models were successfully developed for all analytes bar VCD and transferred to the 15 L scale. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012     

Detecting and quantifying meat meal or meat and bone meal contamination in fishmeal by visible and near infrared reflectance spectra

The use of animal protein feeds such as meat meal or meat and bone meal (MMBM) play an important role in the feed manufacturing industry, but their safe and healthy use in animal feeds is of public concern in order to prevent the spread of bovine spongiform encephalopathy (BSE). The objective of the present work was to develop a technique using near infrared reflectance spectroscopy (NIRS) that would be suitable for detecting and quantifying contaminating levels of MMBM in fishmeal. To this end, a partial least squares (PLS) discriminant analysis and a modified partial least squares (MPLS) quantitative analysis, using visible and NIRS, were developed using a calibration set of 186 samples including 90 samples of pure fishmeal and 96 samples adulterated with MMBM at levels ranging from 10 to 320 g/kg. An external validation set, comprised of 39 pure samples and 54 adulterated samples, was used to validate the calibration model. A PLS discriminant analysis model developed with mathematic pretreatment 1,4,4,1, successfully detected fishmeal adulterated with MMBM. External validation indicated that all samples were discriminated correctly. A MPLS quantitative model, developed with mathematic pretreatment 1,4,4,1, also successfully predicted the MMBM in fishmeal with standard error of cross-validation (SECV) of 27.89 g/kg and ratio of the standard deviation of the validation set to the standard error of prediction (RPD) of 3.37. The calibration and validation results confirm that NIRS could provide the feed industry and inspection bodies with a rapid, non-destructive and non-invasive technique for the detection and quantification of MMBM in fishmeal.     

Inference in morphological taxonomy using collinear data and small sample sizes: Monogenean sclerites (Platyhelminthes) as a case study

Vignon, M. (2011) Inference in morphological taxonomy using collinear data and small sample sizes: Monogenean sclerites (Platyhelminthes) as a case study. —Zoologica Scripta, 40, 306–316. Taxonomists and evolutionary biologists frequently use a combination of morphological measurements to distinguish between species and investigate local adaptation. However, the entire set of characters often displays various degrees of collinearity. This paper discusses the effect of using collinear data in morphological taxonomy and ways to handle multicollinearity in a classification context, with special consideration for small sample size. In addition, I propose a robust and easy‐to‐use combination of dimension reduction using partial least squares (PLS) with traditional discriminant methods for morphological data. To do this, I investigated morphological variation patterns among four monogenean populations from the Pacific Ocean using the correlated morphological features of the sclerotized attachment organ. The new approach yielded better prediction results (lower classification error rates) than the traditional dimension reduction method based on principle component analysis (PCA) and is also much more robust for small sample size. This emphasizes that PLS may be more efficient than PCA in dealing with correlated data and extracting the most relevant morphological differences among groups.     

Vibrational spectroscopy and chemometrics to characterize and quantitate trehalose crystallization

Investigating the phase behavior of sugars in ice and lyophilized solids is of significant interest in the pharmaceutical industry. In this study, Raman and near infrared (NIR) spectroscopy are used to characterize and quantitate trehalose crystallization using several chemometric models. The predictive behaviors of partial least squares (PLS), principal component analysis (PCA), and multiple linear regression (MLR) models are compared. In general, PLS and PCA outperform linear and MLR models. Changes in specific vibrational modes associated with several coupled motions are described and assigned as a function of crystal content. In addition to characterization and quantitation, our method may be used to localize gradients of amorphous and/or crystallized trehalose within a sample.     

Quantitative Determination of the Biodegradable Polymer Poly(β-hydroxybutyrate) in a Recombinant Escherichia coli Strain by Use of Mid-Infrared Spectroscopy and Multivariative Statistics

Fourier transform infrared (FTIR) spectroscopy in combination with the partial least squares (PLS) multivariative statistical technique was used for quantitative analysis of the poly(β-hydroxybutyrate) (PHB) contents of bacterial cells. A total of 237 replicate spectra from 34 samples were obtained together with gas chromatography-determined reference PHB contents. Using the PLS regression, we were able to relate the infrared spectra to the reference PHB contents, and the correlation coefficient between the measured and predicted values for the optimal model with a standard error of prediction of 1.49% PHB was 0.988. With this technique, there are no solvent requirements, sample preparation is minimal and simple, and analysis time is greatly reduced; our results demonstrate the potential of FTIR spectroscopy as an alternative to the conventional methods used for analysis of PHB in bacterial cells.     

Potential of milk mid-IR spectra to predict metabolic status of cows through blood components and an innovative clustering approach

Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R² of calibration of 0.55, 0.69, 0.49 and 0.77, and R² of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.     

Quantitative determination of the biodegradable polymer Poly(beta-hydroxybutyrate) in a recombinant Escherichia coli strain by use of mid-infrared spectroscopy and multivariative statistics

Fourier transform infrared (FTIR) spectroscopy in combination with the partial least squares (PLS) multivariative statistical technique was used for quantitative analysis of the poly(beta-hydroxybutyrate) (PHB) contents of bacterial cells. A total of 237 replicate spectra from 34 samples were obtained together with gas chromatography-determined reference PHB contents. Using the PLS regression, we were able to relate the infrared spectra to the reference PHB contents, and the correlation coefficient between the measured and predicted values for the optimal model with a standard error of prediction of 1.49% PHB was 0.988. With this technique, there are no solvent requirements, sample preparation is minimal and simple, and analysis time is greatly reduced; our results demonstrate the potential of FTIR spectroscopy as an alternative to the conventional methods used for analysis of PHB in bacterial cells.     

Comparison of near infra-red spectroscopy, neutral detergent fibre assay and in-vitro organic matter digestibility assay for rapid determination of the biochemical methane potential of meadow grasses

This paper investigates near infra-red spectroscopy (NIRS) as an indirect and rapid method to assess the biochemical methane potential (BMP) of meadow grasses. Additionally analytical methods usually associated with forage analysis, namely, the neutral detergent fibre assay (NDF), and the in-vitro organic matter digestibility assay (IVOMD), were also tested on the meadow grass samples and the applicability of the models in predicting the BMP was studied. Based on these, regression models were obtained using the partial least squares (PLS) method. Various data pre-treatments were also applied to improve the models. Compared to the models based on the NDF and IVOMD predictions of BMP, the model based on the NIRS prediction of BMP gave the best results. This model, with data pre-processed by the mean normalisation method, had an R² value of 0.69, a root mean square error of prediction (RMSEP) of 37.4 and a residual prediction deviation (RPD) of 1.75.     

An untargeted metabolomic approach in the chemotaxonomic assessment of two Salvia species as a potential source of α-bisabolol

α-Bisabolol is a commercially important aroma chemical currently obtained from the Candeia tree (Vanillosmopsis erythropappa). Continuous unsustainable harvesting of the Candeia tree has prompted the urgent need to identify alternative crops as a source of this commercially important sesquiterpene alcohol. A chemotaxonomic assessment of two Salvia species indigenous to South Africa is presented and recommended as a potential source of α-bisabolol. The essential oil obtained by hydrodistillation of the aerial parts was analysed by gas chromatography coupled to mass spectrometry (GC–MS) and mid-infrared spectroscopy (MIRS). Orthogonal projections to latent structures–discriminant analysis (OPLS–DA) were used for multivariate classification of the oils based on GC–MS and MIRS data. Partial least squares (PLS) calibration models were developed on the MIRS data for the quantification of α-bisabolol using GC–MS as the reference method. A clear distinction between Salvia stenophylla and Salvia runcinata oils was observed using OPLS–DA on both GC–MS and MIRS data. The MIR calibration model showed high coefficient of determination (R² = 0.999) and low error of prediction (RMSEP = 0.540%) for α-bisabolol content.     

Near infrared spectroscopy coupled with radial basis function neural network for at-line monitoring of Lactococcus lactis subsp. fermentation

In our previous work, partial least squares (PLSs) were employed to develop the near infrared spectroscopy (NIRs) models for at-line (fast off-line) monitoring key parameters of Lactococcus lactis subsp. fermentation. In this study, radial basis function neural network (RBFNN) as a non-linear modeling method was investigated to develop NIRs models instead of PLS. A method named moving window radial basis function neural network (MWRBFNN) was applied to select the characteristic wavelength variables by using the degree approximation (Da) as criterion. Next, the RBFNN models with selected wavelength variables were optimized by selecting a suitable constant spread. Finally, the effective spectra pretreatment methods were selected by comparing the robustness of the optimum RBFNN models developed with pretreated spectra. The results demonstrated that the robustness of the optimal RBFNN models were better than the PLS models for at-line monitoring of glucose and pH of L. lactis subsp. fermentation.     

Broad-scale geographic patterns in the distribution of vertically-transmitted, asexual endophytes in four naturally-occurring grasses in Sweden

The presence and distribution of vertically-transmitted, asexual Neotyphodium/Epichloë endophytes in four species of widely distributed grasses, all members of the sub-family Pooideae, were determined at 57 spatially-distinct sites across Sweden in naturally-occurring grass populations. While these endophytes are well-studied in agricultural systems, much less is known about their abundance and distribution in non-agricultural systems at larger scales across landscapes. We used two screening methods to detect endophytes: 1) visual inspection of fixed, stained grass shoots, and 2) immunoblot cards with monoclonal antibodies specific for Neotyphodium / Epichloë endophytes. Infection frequency (i.e. the proportion of individuals) varied widely among species and among sites, a finding common to most studies performed in non-agricultural ecosystems. Festuca rubra had the highest overall infection frequency (23% visual screening, 27% immunoblot screening), while Deschampsia flexuosa (4%) and Poa trivialis (4%) had low frequencies of infection. None of the sampled Agrostis capillaris populations were infected. In F. rubra , the within-site infection frequency varied from 0 to 100%. A significant altitudinal gradient was found for F. rubra , with the infection frequency of the vertically-transmitted endophyte Epichloë festucae decreasing with increasing altitude above sea level. The high variation across and within grass species at different geographical locations that ours and others' studies reveal, agree with suggestions that agronomic model systems cannot be readily extrapolated to understand the ecological role of endophytes in native grasses in the wild. Further investigation into the underlying cause of the observed altitudinal gradient is required to understand broader-scale patterns in the distribution of endophyte-infected grasses.