Author: naturehydro

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Cereals are inherently low in protein and mineral micro-nutrients such as Fe and Zn

When necessary, data was transformed using power transformations to satisfy ANOVA assumptions. Hydroponic experiments were performed in growth chambers at 22-23 °C with a photoperiod of 16 h light / 8 h dark provided by fluorescent lights supplemented with incandescent lighting. In all experiments, grains were imbibed at 4°C for four days, after which they were placed at room temperature. Once most of the grains had germinated and the coleoptiles had emerged, healthy seedlings were transferred to a mesh suspended on water or CaCl2 . Four days later, healthy seedlings were transferred to tanks with growth solutions 6Mo7O24.4H2O 0.05 M, CuSO4.5H2O 0.5 M, ZnSO4.7H2O 1 M, MnSO4.H2O 1 M, FeEDTA 0.1 mM, Ca2 1.0 mM, 2SO4 1.0 mM. After removing the grain, seedlings were wrapped at the crown with foam and inserted in holes pre-cut in a foam core board placed on top of the solution. Nutrient solution was changed two to three times a week for the duration of the experiment. Particular details of the methods used in the two laboratories are described below: Davis, CA, USA: The experiments were performed in 13 L hydroponic tanks containing the nutrient solution. Twenty-four seedlings were placed in each tank in a six by four pattern. All genotypes were included in one tank and, if necessary, multiple tanks were used as replications. In the experiments to study the effect of different nitrogen sources and concentrations , seedlings were grown in normal growth solution for seven days and then transferred to four separate tanks with each of the four nitrogen sources for 10 days . Roots were measured at 22 DAG. Each tank included 6 replications of each of the four genotypes organized in a completely randomized design. The results were analyzed in a 2 x 2 factorial ANOVA with distal and proximal 1RS regions as factors and wheat or rye chromosome segments as levels. For the analysis of distances between the first lateral roots and the RAM, round plastic planter the four genotypes were grown in a tank with normal nitrogen conditions in a completely randomized design . Lines carrying distal rye or wheat segments were compared using a t-test. Chascomús, Buenos Aires Argentina: The CaCl2 from the germination tank was replaced by nutrient solution on the 4th day. On the 5 th day, plants were transferred to 350 mL pots containing nutrient solution, with each pot being a replicate.

Pots were rotated every two days to ensure that they occupied different positions within the growth chamber. For the root elongation time course, the length of the second longest seminal root was measured daily four hours after the start of the light period, starting 6 DAG. Within each experiment, data was analyzed as repeated measures . A combined ANOVA was performed using experiments as blocks. Previous studies have shown an association between the introgression of the rye 1RS arm in wheat and improved resistance to water stress . In three of these studies, the 1RS.1BL lines showed increased root biomass compared to the non-1RS control lines in large pot or sand-tube experiments. However, these differences were not validated in the field. In this study we showed that differences in grain yield and biomass between plants carrying a complete 1RS translocation and NILs with an introgressed distal wheat chromosome segment are associated with differences in total root length density and average root diameter in the field. Field excavations of the four different 1RS NILs provided an opportunity to visualize the differences in their root systems and to quantify these differences using horizontal soil cores at consistent depths. This experiment confirmed the hypothesis that the 1RSxR lines have a higher root density throughout the soil profile, with roots that reach deeper in the soil than the 1RSxW lines . The more extensive root system of the 1RSxR lines relative to the 1RSxW lines may have contributed to their better tolerance to drought and water logging conditions in the experiments presented in this study , and to the higher carbon isotope discrimination and increased stomatal conductance values detected in a previous study . Through their deeper root system, the 1RSxR plants can access more stored soil moisture and nutrients, keep their stomata open longer, and generate additional photosynthetic products and biomass than the 1RSxW plants. However, we cannot rule out the possibility that the genes in the distal 1BS introgression may have a more direct effect on aerial biomass or on other anatomical and/or physiological root differences known to impact tolerance to water logging and drought .

The differences in root depth observed between the Hahn 1RSxR and 1RSxW NILs in the field were paralleled by drastic changes in seminal root length in hydroponic cultures . These differences were robust across experiments and were detected with different nitrogen sources and concentrations . We hypothesize that these early differences in seminal root length may have contributed to the observed differences in total root length density observed in the deepest soil core samples in the field . The early and consistent differences in root growth under controlled conditions provided the opportunity to study the process in detail. During the first week of development, root growth occurred at the same rate for both genotypes, suggesting that the differences were not primarily associated with embryonically determined differences in root elongation. Instead, differences in root growth consistently manifested during the second week across multiple experiments. The growth rate of the seminal roots of the 1RSxW plants gradually decreased during the second and third week, to come close to zero by the end of the third week, whereas growth continued in the 1RSxR plants . The consistent timing of these events suggests that these changes are developmentally regulated. The growth arrest of the seminal roots in the 1RSxW plants was accompanied by the proliferation of lateral roots in close proximity to the RAM, suggesting important changes in the RAM. The RAM consists of a quiescent center surrounded by stem cells that generate new daughter cells, which undergo additional divisions in the proximal region of the meristem and differentiatein the transition zone . At a cellular level, a balance between cell proliferation and cell elongation/differentiation determines root growth rate . The arrest of the growth of seminal roots in 1RSxW plants suggests a modification in cell proliferation and/or cell elongation/differentiation. Additional studies will be required to determine if this arrest involves changes in the QC and/or modifications in the root regions adjacent to the meristem. In any case, the dramatic reduction in seminal root growth and increased lateral root proliferation close to the RAM argues for an early developmental program switch in the regulation of the RAM in the 1RSxW plants.

The transition from cell proliferation to cell elongation and differentiation and the subsequent development of lateral roots depends on the distribution of ROS along the root axis, specifically on the opposing gradients of superoxide and hydrogen peroxide. Superoxide is predominant in dividing cells in the meristematic zone, while hydrogen peroxide is predominant in elongated cells in the differentiation zone . The balance between these ROS modulates the transition between root proliferation and differentiation zones. Seventeen days after germination,round plastic plant pot the apical region of 1RS seminal roots showed opposing gradients of superoxide and hydrogen peroxide characteristic of elongating roots . A different ROS distribution was detected in the arrested 1RSxW roots, where superoxide was restricted to the distal ~700 m and increased levels of DCF-DA fluorescence were detected between 250-950 m in the cell proliferation zone . The contrasting patterns of ROS distribution reflect the major developmental changes that differentiate the seminal roots of the 1RS and 1RSxW genotypes. Studies in Arabidopsis have shown that changes in ROS distribution can be triggered by the altered expression of major genes that control the size of the meristematic zone. These genes include UPBEAT1 , a basic helix-loop-helix transcription factor that regulates the meristematic zone size by restricting H2O2 distribution in the elongation zone . In addition, ROOT MERISTEM GROWTH FACTOR 1and the transcription factor RGF1 INDUCIBLE TRANSCRIPTION FACTOR 1that mediates RGF1 signaling can modulate the distribution of ROS along the root developmental zones leading to enhanced stability of PLETHORA2 . Reduced expression of PLETHORA in the root apical region or changes in its distribution have been associated with impaired root growth. To test if these Arabidopsis results are applicable to wheat, we are initiating expression studies of these genes in the 1RSxR and 1RSxW lines. It remains unknown if the differential pattern of ROS distribution in the roots of the 1RSxW plants is the result of changes in the wheat homologs of these central developmental genes or a more direct effect on genes affecting the redox balance in different developmental root zones. The differences in superoxide and hydrogen peroxide distribution between the seminal roots of the 1RSRW and 1RS plants were measured after the arrest in root growth . Therefore, we currently do not know if the changes in ROS distribution are a cause or consequence of the changes observed in root growth and lateral root proliferation close to the RAM. Wheat is a crop of major importance and together with other staple cereals supply the bulk of calories and nutrients in the diets of a large proportion of the world population . A major focus of wheat breeders has been grain protein concentration as it affects bread- and pasta-making quality, but micro-nutrient improvement has received less attention. Approximately half of the world’s population suffers from Fe and/or Zn deficiencies and millions of children suffer from protein-energy malnutrition . As such, the improvement of nutritional quality of wheat could benefit the nutritional status of millions of people. A common agronomic practice to increase grain protein concentration is the use of N fertilization. However, this practice is expensive and excess fertilizer run-off is a potential environmental contaminant .

A substantial percentage of the N in wheat grain is supplied by amino acids remobilized from vegetative tissue . Much of this N content is derived from proteins that are disassembled and recycled during the leaf senescence stage of development . Likewise, Fe and Zn have been shown to be remobilized from vegetative tissues in several plants , although the specific sources are unknown. Zinc fertilization has been a successful strategy to improve wheat grain Zn concentration , and improvement in the partitioning or remobilization of Zn to grain could make fertilization efforts more efficient. Wheat grain with higher Zn concentration has been demonstrated to produce more vigorous crops . Thus, breeding or transgenic approaches that result in plants with increased partitioning of minerals to grain could be useful for both nutritional bio-fortification and reduced fertilizer application. Chromosome 6B from wild emmer wheat was identified as a potential source of genetic variation for grain protein , Zn, and Fe concentration . A quantitative trait locus for grain protein concentration was mapped on chromosome arm 6BS and later mapped as a single Mendelian locus, Gpc-B1 . In near-isogenic lines of this locus, increased grain protein was associated with the increased remobilization of amino acids from the flag leaf , higher grain Fe and Zn concentrations , and accelerated leaf yellowing, indicating accelerated senescence . A NAC transcription factor, NAM-B1, was identified as the causal gene for Gpc-B1 by positional cloning . Other members of the NAC family are known to regulate developmental processes , including leaf senescence . In transgenic wheat NAM RNA interference lines in which NAM-B1 and its homeologous genes had decreased expression, leaf yellowing was delayed, and grain protein, Fe, and Zn concentrations were greatly decreased . These results, together with higher N, Fe, and Zn concentrations in RNAi line flag leaves at maturity, suggested a role for NAM-B1 homeologues in the remobilization of N compounds, Fe, and Zn. However, without taking organ mass, nutrient concentrations at prior time points, and total nutrient accumulation of other organs into account, this model could not be confirmed. In addition, the body of literature does not contain sufficient data regarding sources of grain minerals to support the idea that remobilization alone could account for the differences observed. Because a whole-plant partitioning profile has not been undertaken in plants differing in NAM-B1 expression, it is currently unclear whether this gene directly affects remobilization , alters partitioning of nutrients within the plant, alters total plant uptake of these nutrients, or influences a combination of these processes.

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Human norovirus is one of the major causes of acute gastroenteritis worldwide

Elevated temperatures cause an increase in transpiration as the plant’s mechanism to decrease leaf temperature . However, prolonged transpiration and dry soil conditions may alter a plant’s strategy to mitigate heat stress due to the need to conserve water. Considering that we saw an increase in ABA content with increased CEC concentrations, we speculated that the cucumber plant’s ability to adapt and mitigate heat stress would be further impaired due to exposure to CECs. The ABA content in cucumber tissues followed the same general trend under heat stress conditions as it did under non-heat stressed conditions . No differences in root ABA content due to heat stress were observed within the treatments, however the 1X and 20X CEC treatment with heat stress were significantly decreased from the control with heat stress . Similarly, significant differences in leaf ABA content due to heat stress were not observed within the same CEC treatment, but did show a consistent elevated trend across the range of CEC treatment levels when the plant was also subjected to heat stress. It must be noted that only a 4 d heat stress with somewhat moderate, but realistic, temperature regimes was examined in this study. If this observed trend were to continue, it could have a significant effect over the long-term health and development of the plant. It is possible that prolonged exposure to heat stress and the resulting increase in abscisic acid content and anti-transpiration activity could ultimately affect biomass production and water use efficiency.The virus is a leading cause of food borne illness in the United States,25 liter pot causing nearly 58% of foodb orne disease . Fresh produce has been identified as a leading cause of food borne illness and is a major high risk food associated with human NoV outbreaks in the US . Vegetable row crops and fruits were responsible for 30% and 21%, respectively, of human NoV food borne outbreaks in the US .

Vegetables and crops can be contaminated with human NoV at any point from farm to fork. Evidence has shown that the source of pre-harvest contamination mainly comes from soil, fertilizer, or irrigation water. Though human NoV is a major contributor to fresh produce associated outbreaks, the modes of contamination and persistence of the virus in vegetables remains poorly understood. Human NoV is a non-enveloped single stranded positive sense RNA virus of the family Caliciviridae . The major challenge in human NoV research is that currently there is no robust cell culture system for the virus. Recently, two cell culture systems were developed for human NoV, but have not yet been optimized to produce high viral titers . Therefore, much of the understanding of human NoV molecular biology, pathogenesis, and environmental stability has come from the study of surrogate viruses . Many viruses within the family Caliciviridae have been utilized as human NoV surrogates, including murine norovirus , feline calicivirus , and Tulane virus . Tulane virus is a newly recognized surrogate for human NoV and is member of the genus Recovirus within Caliciviridae . TV was shown to have similar pH stability to human NoV and other surrogates at ranges from pH 3 to pH 8 . TV causes enteric infection in primates and also recognizes histo-blood group antigens as a cellular attachment receptor, similar to human NoV . Internalization of pathogens in growing produce is considered one of the potential routes for contamination of fresh produce . Bacterial pathogens, such as Salmonella enterica serovar Typhimurium and Esherichia coli O157:H7, have been shown to be internalized in vegetables including lettuce, radishes, alfalfa and green onions . Human NoV has also been shown to be internalized in growing produce such as lettuce, spinach, and green onion . However, few studies exist where multiple types of produce have been evaluated for viral internalization in parallel. In addition, the influence of initial inoculum levels on viral internalization in different types of produce has not been evaluated extensively.

In this study, green onion, radishes, and Romaine lettuce were selected to evaluate the effect of growth matrix, inoculum level, and vegetable type on the internalization of human NoV and TV in fresh produce. Human NoV GII.4 strain 707 was originally isolated from an outbreak of acute gastroenteritis in Ohio. The virus genomic RNA was quantified by reverse transcriptase quantitative PCR and then stored at −80 °C. TV was generously provided by Xi Jiang at Cincinnati Children’s Hospital. TV was propagated in confluent monolayers of the monkey kidney cell line MK2-LLC . MK2-LLC cells were cultured at 37 °C in a 5% CO2 atmosphere in low serum Eagle’s minimum essential medium supplemented with 2% FBS. Before virus infection, MK2-LLC cells were washed with Hanks’ balanced salt solution and subsequently infected with TV at an MOI of 1. After 1 h of incubation at 37 °C, 18 ml of Opti-MEM with 2% FBS was added. The virus was harvested 2 days post infection by three freeze thaw cycles followed by centrifugation at 3000 × g for 10 min to remove cell debris. After centrifugation, the supernatant was collected and virus stocks were stored at −80 °C. TV titer was determined by plaque assay. Seeds of green onion and radish were purchased from Livingston Seed and stored at 4 °C. Before sowing, the seeds were soaked for 1 day at room temperature in a 500 ml beaker of tap water. Subsequently, the water was drained and the seeds were covered with 2 layers of wet Kim wipes for 2 days to accelerate seed germination. After germination, the seeds were planted in 4 inch plastic pots and grown in plant growth chamber under long day conditions in Metro-Mix® 300 soil . Two month old green onions and Romaine lettuce and one month old radishes were used for experiments. For growth in the hydroponic system, plants were removed from soil and roots were washed thoroughly with tap water to remove soil and then placed in racks above feed water. Feed water was aerated using a pump and antibiotics were added to limit microbial growth. The feed water was not replaced during the study period.

After viral inoculation, only the roots contacted the feed water and a plastic barrier separated the aerial plant tissues and feed water to limit cross contamination. For green onion grown hydroponically, TV was diluted in feed water to result in a high titer and low titer virus concentration in the feed water. Human NoV was diluted in the feed water of hydroponically growing green onions to achieve 1.0 × 105 RNA copy/ml. For hydroponically grown radishes, only the high concentration of TV was tested. For each treatment group, a 10 ml sample feed water was collected before plants were inserted and was used a control to determine the stability of TV in feed water without plants. In addition, uninoculated control groups were set up for each treatment group. The total volume of the hydroponic feed water following virus dilution was 400 ml and the initial virus titer was determined using plaque assay or RT-qPCR . Negative control plants were kept in separate tanks and no virus was added. At days 0 , 1, 3, 7, and 14, four plants were harvested for each condition and a sample of the feed water was collected. To minimize cross contamination, the upper most leaves were harvested first, followed by shoots, and roots were harvested last . Harvested tissues were placed in individual sterile plastic bags and each tissue was weighed. Next,25 liter plant pot the surface of each tissue was decontaminated by submersion in 1000 ppm chlorine followed by rinsing with water and inactivation of residual chlorine with 0.25 M sodium thiosulfate. Samples were then homogenized by grinding with mortars and pestles with 5 ml PBS . Sample homogenates were transferred to 15 ml tubes and centrifuged at 3000 × g for 10 min to remove cellular debris and the virus-containing supernatant was then transferred to a new collection tube. No virus concentration step was performed prior to detection. Detection of viruses in plant tissue samples and feed water samples was determined by RT-qPCR and plaque assay . The detection limit for RT-qPCR was determined to be 5 RNA copy/ml using dilution of plasmid standard in each sample matrix. The detection limit for plaque assay was determined to be 10 PFU/ml by diluting TV stock in each sample matrix. Three technical replicates were executed during RT-qPCR analysis and two technical replicates were used for plaque assay for each sample. The consumption of fresh fruits and vegetables continues to increase in many countries and fresh produce is an important vehicle for food borne disease transmission. The outbreaks associated with fresh produce have resulted in considerable public health and economic burdens .

Among the pathogens associated with fresh produce outbreaks, an increased incidence of infections and outbreaks are attributed to food borne viruses, most notably human NoV . It has been demonstrated that various types of plants are susceptible to internalization of human viral pathogens during growth . Various factors have the potential to affect the ability of human pathogens to internalize in growing plants including the growth substrate , plant developmental stage, pathogen type, inoculum level, plant species and cultivar, abiotic and biotic stresses . In this study, different plants types, inoculum levels, and growth matrices were tested to determine their effect on the internalization and dissemination of human NoV. Previous research has shown that the level of pathogen inoculum used to contaminate plants can greatly influence the rate of bacterial internalization and dissemination . For example, in Arabidoposis thaliana, low inoculum levels of Salmonella Typhimurium were able to colonize the root surface but did not invade the lateral root junctions. When the inoculum level was increased to 106 CFU/mL, the bacteria were able to internalize into the root . In this study, two different levels of TV inoculum, high and low , were used to contaminate the feed water of hydroponically growing green onions. TV was detected in roots of green onions in both the high and low inoculum groups. The high inoculum group had infectious virus detected in the aerial portions of the plant while no virus was detected in these tissues when a low virus inoculum was applied. Unlike bacteria that have the ability to replicate in the phyllosphere, viruses are unable to replicate outside of their host cell. However, in general it would be expected that higher inoculum levels would result in higher levels of internalization . This was the conclusion made in another study in which higher inoculums of E. coli O157:H7 in spinach showed higher contamination incidences . In another study, the internalization of Salmonella Typhimurium was highly dependent on the concentration of the pathogen present in irrigation water. Irrigation water containing 5 Log CFU/mL Salmonella Typhimurium resulted in limited incidence of internalization in lettuce, while 8 Log CFU/mL Salmonella Typhimurium in the irrigation water, significantly increased the internalization frequency. Similar to these studies, we found that increased TV contamination levels in green onions lead to increased internalization of the virus in hydroponically grown green onion. In addition, we evaluated the internalization of human NoV in hydroponically growing green onion. We found that high levels of human NoV RNA were detected in all harvested green onion tissues starting on day 1 post inoculation. The levels of RNA decreased over the study period; however RNA was still detectable in all tissues on day 14 post inoculation. The data indicates that human NoV internalized via the root of the green onions and transports to the leaves. We also used RT-qPCR to evaluate the level of internalized TV RNA in this study. We found that high levels of TV RNA were detected starting on day 1 post inoculation and that the level of RNA remained at this level at all subsequent time points. However, this differs from the internalization results obtained for TV using plaque assay as the method of detection, in which lower levels of internalization were detected and there were reductions in the level of virus internalized at later time points. This could be due to the fact that RT-qPCR is more sensitive than plaque assay and that RNA detection alone may not accurately reflect the recovery of infectious viruses in these samples.

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Nitrate-supplied plants accumulated the greatest amounts of nutrients at ambient CO2

The shoot biomass data suggest that growth differences measured early in the lifespan of wheat supplied with NH4 + or NO− 3 or NH4 + do not necessarily carry through to senescence. This may be due in part to a shift in NO− 3 assimilation to the root , allowing NO− 3 -supplied plants to compensate for the decrease in shoot NO− 3 assimilation that occurs at elevated atmospheric CO2 concentrations . The decrease in yield and biomass measures at elevated CO2 concentrations does not agree with field observations where wheat yields as well as overall biomass increased with elevated CO2 . Similarly, our results that the greatest values for other yield measures occurred at ambient CO2 concentrations varies from the literature. High CO2 has been found to increase flowering tillers , KN , and kernel mass . Conflicting results, however, have also been reported . Many of the field and open top chamber studies were grown under natural light and thus received substantially greater photosynthetic flux density than our chamber-grown plants. These higher light conditions would be more favorable to biomass accumulation. Also, these studies typically applied high amounts of mixed N fertilizer , and yields and biomass have been found to be greater under mixed N nutrition than under either NH4 + or NO− 3 alone . Finally, the wheat cultivar we used is a short-statured variety that has rarely been used in other studies and may have accounted for some of the differences between our study and other published data. Our results that NH4 + -supplied plants had greater yield and yield components than NO− 3 -supplied plants at ambient CO2 have been observed previously . Wang and Below observed greater numbers of kernels head−1 and KN in plants supplied NO− 3 that was not observed here. Their study, however, supplied NH4 + at relatively high levels . Several studies have found that incipient NH4 + toxicity can start appearing at N levels as low as 0.08–0.2 mM NH4 + ,vertical farming equipments although the onset of NH4 + toxicity depends on light level and solution pH . The poorer performance of the NH4 + treatment in Wang and Below , therefore, might derive from NH4 + toxicity.

We have previously determined that the 0.2 mM NH4 + -supplied to our plants to be sufficiently high for normal growth, but low enough to avoid toxicity problems under our experimental conditions . Our second hypothesis, that nutrient concentrations are differentially affected by the inorganic N form supplied to the plants and CO2 enrichment, was supported by our data. CO2 concentration and N form interactions may alter tissue demands for nutrients. For many nutrients, ratios between different elements are typically maintained within a narrow range . CO2 concentration and N form may disturb the balance between different nutrients, leading to a cascade of changes in demand, accumulation, and allocation among the different plant tissues .Some portion of the greater response of NH4 + -supplied plants to CO2 derived from a dilution effect from the greater biomass at ambient CO2 concentrations . Total amounts of nutrients tended to decline with CO2 enrichment for NH4 + -supplied plants, which had the greatest amounts of macro/micro-nutrients at sub-ambient CO2 . These results have not been observed in other published studies . Growth chamber studies, however, tend to have more exaggerated differences among treatments than field and greenhouse experiments , and N source cannot be well-controlled in field and greenhouse experiments. The observed increase in NO− 3 −N concentration with CO2 concentration in NO− 3 -supplied plants has been reported previously , and adds further support to the hypothesis that elevated CO2 concentrations and the resulting decrease in photo respiration inhibit shoot NO− 3 photo assimilation. Nevertheless, tissue NO− 3 − N concentrations observed here were substantially lower than those in the earlier study . Again, this may derive from difference in life stages in the two studies. Most of the N available to the plant for grain filling comes from N translocation rather than uptake from the substrate . Probably, the plants continued to assimilate plant NO− 3 using a non-photo respiratory dependent process such as root assimilation after root N uptake slowed or stopped. Loss of NO− 3 through root efflux to the nutrient solution also may have contributed to the lower concentration of NO− 3 − N.

The partitioning and accumulation of all mineral elements was affected in some manner by the CO2 treatment and N form supplied to the plants. Observations that cation concentrations decrease under NH4 + supply relative to NO− 3 supply were not apparent in this study. Again, this could be partly due to the relatively low concentration of NH4 + -supplied in our study, the age of the plants at harvest, and differences among wheat cultivars. Allocation of nutrients within the plant followed similar trends for both N forms, with the exceptions of Mn and Cu . Interestingly, in NO− 3 -supplied plants, shoot Mn concentrations increased slightly with CO2, and these plants allocated far more Mn to the shoots than NH4 + -supplied plants at all CO2 concentrations. Manganese has been found to activate Rubisco in place of Mg2+ and the Rubisco-Mn complex has been observed to decrease Rubisco carboxylase activity while minimally affecting or even enhancing oxygenase activity . The slight increase in shoot Mn with CO2 corresponded to a large 23% decrease in Mg concentration. Manganese, which can act as a cofactor for glutamine synthetase , was also the only nutrient that NH4 + -supplied plants allocated a greater percentage to the roots at the expense of the shoots. NO− 3 – supplied plants typically allocated a higher percentage of most nutrients to the roots, as has been reported previously . Phytate, which forms complexes with divalent cations, has been found to hinder human Zn and Fe absorption during digestion and thus has been labeled an “anti-nutrient.” It may serve a number of valuable functions, however, including roles as an anti-oxidant and anti-cancer agent . Phytate is also the major repository of grain P, and variation in P supply to the developing seed is the major determinant of net seed phytate accumulation . To our knowledge, no published studies have explicitly looked at how phytate is affected by CO2 concentration. Elevated CO2 has been found to have a much larger negative impact on Zn and Fe concentrations than on P in wheat .

Several studies have observed that P increases slightly with CO2 concentration, and because the majority of P is tied up in phytate, this may cause increases in grain phytate concentrations as atmospheric CO2 rises. As a result, bio-available Zn and Fe–Zn and Fe not bound to phytate – is expected to decrease even further . Nonetheless, we did not observe such trends in macro- and micro-nutrient concentrations in this study. The mechanism behind these contrasting results is not clear, although the environmental conditions and nutrient solution in which the plants were grown likely had some role. The modeled data demonstrated only a small negative impact of CO2 concentration on bio-available Zn concentrations , which was unexpected. Indeed, the grain from NO− 3 -supplied plants actually showed a slight increase in bio-available Zn between ambient and elevated CO2. These results combined with the differences in grain bio-available Zn between NH4 + and NO− 3 -supplied plants demonstrates that N form may differentially affect the nutritional status of this important nutrient, especially in less developed countries that might be more dependent on phytate-rich grains for their Zn nutrition . The milling process removes some, if not most, of the phytate and grain mineral content with the bran fraction of the grain . Regardless, with over 50% of the human population suffering from Zn deficiencies, even small increases in bio-available Zn would be beneficial . This modeling exercise, however, is not a prediction of how increasing CO2 will affect wheat nutrition so much as illustrates that N source may mediate, to some extent, the effects of CO2 on phytate and bio-available Zn, and that N source will become an even more important agricultural consideration in the future. In summary, both CO2 concentration and N form strongly affect biomass and yield in hydroponically grown wheat, as well as nutrient concentrations in above- and below ground tissues. Interactions among plant nutrient concentrations,CO2 concentrations,vertical grow system and N form are complex and non-linear. The impact of N form and CO2 concentration on the mechanisms affecting nutrient accumulation and distribution requires further research and extension to more realistic and agriculturally relevant growing conditions found in greenhouse and field studies. Of course, in greenhouse and field studies, control of N source is limited and control of atmospheric CO2 concentration is expensive. The effects of CO2 and N form on agriculture and human nutrition observed here are interesting and suggest a new area of research on mitigating the effects of climate change on agriculture. The supply of fertilizers or addition of nitrification inhibitors that increase the amount of available NH4 + may have beneficial effects for human nutrition, particularly in regards to micro-nutrient deficiencies such as Zn and Fe that currently affect billions of people worldwide. In the face of the potentially negative consequences of climate change on agriculture, all avenues of mitigation must be examined, and even small improvements may prove worthwhile.Features of the seven-story Paharpur Business Center and Software Technology Incubator Park in New Delhi India have been described. A notable feature of the building is the stated goal of providing a healthy work environment for building occupants with specific interest in maintaining superior indoor air quality.

To achieve this goal, the building utilizes several innovative air cleaning technologies, such as air washing to remove the more polar volatile contaminants, bio-filtration of building makeup air using an enclosed rooftop greenhouse with a high density of potted plants, passive treatment of indoor air using a large number of potted plants distributed throughout the building, dedicated secondary heating, ventilation and air conditioning air handling units on each floor with re-circulating high efficiency filtration and ultraviolet light treatment of heat exchanger coils, and air exhaust via the restrooms located on each floor. The idea of using potted plants to remove VOCs from the indoor environment was originally introduced by Wolverton et.al.. In addition to treating the air, the PBC management recognizes the importance of reducing potential sources of indoor chemicals by providing environmentally friendly cleaning products exclusively for the building and selecting certain materials during renovations including a combination of stone, tile and ‘zero VOC’ floor covering and solid sawn wood materials for trim, paneling and furniture, with minimal use of composite wood products. A recent short-term field study collected indoor air quality measurements at the PBC to investigate the performance of the bio-filtration air cleaning system. The study focused primarily on VOCs and aldehydes and collected measurements at several locations in the building representing the transfer pathway of air moving through the building starting on the roof outdoors and following through the rooftop greenhouse, indoors on two floors, and at the building exhaust locations. The study found that for most contaminants, the levels of common indoor VOCs and aldehydes generally increased as the air moved through the building, indicating the presence of indoor sources. The study concluded that even with the extensive effort given to maintaining superior IAQ, the building still had concentrations of VOCs and carbonyls similar to that found in other office buildings. However, the authors point out that given the outdoor air quality in New Delhi compared to the outdoor air quality where the comparative IAQ studies have been carried out for other office buildings, the findings of the short-term study may indicate some added benefit of the bio-filtration-based air cleaning technology. The increase in concentration for several VOCs and carbonyls as the air moved through the building indicated the presence of an indoor source for these chemicals. The contribution of indoor chemicals from different building materials and building contents have been investigated for a range of building types and typical concentrations measured in these buildings have been summarized. The purpose of this project was to investigate the potential source of VOCs and carbonyls in the PBC.

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Containers with plants grown in non-spiked nutrient solution were included as blank controls

All plant treatments were created in quadruplicate and solution treatments were created in triplicate. Laboratory blanks were included with each sample extraction and pure methanol was analyzed in each UPLC/MS/MS run to check potential contamination. Surrogates were used in all sample analyses to account for losses during extraction and matrix effects during instrumental analysis. Recovery of the surrogates was used to calculate the actual concentration of each target analyte. Recoveries of surrogates in plant tissue and nutrient solution samples are listed in Table S5.1 of the Supporting Information. Statistical analysis of data including ANOVA with Tukey’s Honestly Significant Difference, linear regression, and t-test was performed using R . Significance was assigned at p ≤ 0.05. Carrot, lettuce, and tomato plants grown in both environments were found to be generally healthy, and no difference in biomass was detected between plants grown in solution with or without PPCP/EDCs. For the same plant species, those from the warm-dry environment generally had greater bio-masses. One tomato plant from the cool-humid treatment had yellow, stunted leaves and was excluded from the analysis. The nutrient solution pH was measured at each solution exchange, and was found to average pH 5.2 for carrot, pH 5.3 for lettuce, and pH 6.0 for tomato during the study. The average pH values were used to calculate the neutral fraction and the pH-adjusted octanol-water partition coefficient for the different PPCP/EDCs, as described in Wu et al. . Only small differences in neutral fractions and log Dow values were seen between treatments for the same compound,vertical vegetable tower mostly for compounds with pKa values near the solution pH. Based on the primary ionic state in the nutrient solution, the selected PPCP/EDCs were placed in either the anionic, cationic, or neutral group .

The transpired mass for each plant was measured at every solution exchange and the data were used to calculate the cumulative transpiration . For lettuce and tomato, the different temperatures and air humidity resulted in significantly different transpired masses . The differences were smaller for carrot seedlings , likely due to the considerably smaller leaf masses of the carrot plants. The mean transpired masses in the cool-humid and warm-dry treatments during the 21 d of growth were, respectively, 65.50 ± 19.36 and 194.33 ± 30.72 g/d for lettuce, 127.04 ± 15.52 and 503.38 ± 59.76 g/d for tomato, and 16.82 ± 8.05 and 55.31 ± 26.41 g/d for carrots. For the same plant type, the warm-dry environment induced a 3-4-fold increase in plant transpiration as compared to the cool-humid environment. The dissipation of PPCP/EDCs from nutrient solution during the hydroponic growth of plants may be attributed to plant uptake and microbial degradation in the solution. The change in PPCP/EDC concentrations was measured on day 10, after 2 d incubation. In the spiked nutrient solutions without plants, most PPCP/EDCs showed limited dissipation from the solution , suggesting that these compounds were mostly stable in the nutrient solution . The only exception was atorvastatin, where 49.0% and 61.7% were not recovered for the cool-humid and warm-dry treatments, respectively . In the presence of plants, levels of PPCP/EDCs in the solution significantly decreased compared to the plant-free control. For example, after exposure to a tomato plant, about 38.8% of the initially spiked diclofenac was not recovered from the solution for the cool humid treatment and about 75.6% for the warm-dry treatment, while there was essentially no chemical loss in the plant-free container . When all compounds were pooled, removal from the solution was found to be consistently greater in the warm-dry treatment than in the cool-humid treatment. This difference was statistically significant for lettuce and tomato , but not for carrot , likely due to its very small biomass. For example, in the cool-humid and warm-dry treatments, the respective losses of gemfibrozil were 18.2% and 28.6% for carrot, 64.5% and 89.2% for lettuce, and 55.6% and 91.8% for tomato .

These trends clearly suggested that the warm-dry environment and the corresponding larger plant biomass in the warm-dry treatments, contributed to enhanced PPCP/EDC dissipation in the nutrient solution . The transpired mass over the 2 d period was compared to the measured removal of the anionic, cationic, or neutral PPCP/EDCs over the same period to assess the effect of plant transpiration on the removal of PPCP/EDCs from the nutrient solution. A significant positive relationship was found for each group of compounds , suggesting that the removal of PPCP/EDCs in the nutrient solution increased with transpiration for both ionic and neutral compounds, and across different plant species. The separation of PPCP/EDCs by ionic state in the regression analysis decreased the model residuals for both the cationic and neutral groups, as compared to a linear regression with all compounds grouped together , showing that consideration of ionic states better describes the interaction of PPCP/EDC and transpiration. Transpiration had the greatest impact on removal of neutral compounds, as shown by a slope of 0.048 for the linear regression , followed by anionic compounds , while removal of cationic compounds was least affected by transpiration . Since neutral compounds are expected to move through root membranes according to diffusion, and ionic compounds are subject to electrical effects, it is reasonable to expect that transpiration exerts the most effect on neutral compounds. Other compound characteristics besides ionic state, such as hydrophobicity and stability, may also influence PPCP/EDC dissipation in the nutrient solution and may help explain the remaining regression residuals. To evaluate the contribution of adsorption to root structures, log Dow values for each group of compounds were compared to their removals in the nutrient solution. However, no significant relationship was found for any of the treatments , suggesting that log Dow alone was not a good predictor for PPCP/EDC removal from the nutrient solution. It must also be noted that due to the small number of compounds in the cationic group, the analysis may not be sufficiently strong to be generalized for other cationic PPCP/EDCs.

To facilitate comparisons of PPCP/EDC accumulation among different compounds and between different treatments, a bio-concentration factor was calculated by dividing the concentration of a compound in a plant tissue after the 21 d cultivation to the concentration in fresh solution . In this study, atorvastatin, diclofenac, and clofibric acid were the least accumulated , while perfluorooctanoic acid, diazepam, and diuron were the most accumulated compounds . After averaging across all compounds and plant types, BCF values for root tissues were found to be significantly higher than those for leaves , with the respective mean BCF values of 51.3 and 21.0. These BCF values suggest that many PPCP/EDCs have the ability to bio-accumulate in plant tissues, and the overall accumulation into roots likely exceeds that into leaves. In addition, some PPCP/EDCs may be accumulated to relatively high levels. In general, BCFleaf values followed the order cationic ≥ neutral > anionic and BCFroot values were in the order anionic > neutral ≥ cationic,vertical farming equipments suggesting that accumulation of cationic and neutral compounds was somewhat similar. However, anionic compounds were accumulated significantly less than cationic or neutral compounds in leaves, but significantly more in the roots. The reversed trends of accumulation between leaf and root tissues were mainly caused by the behavior of anionic compounds. For anionic PPCP/EDCs, accumulation in root was significantly more than in leaf , with the mean BCF root at 72.8 while the mean BCFleaf at 3.3. In comparison, accumulation into leaf and root tissues was similar for cationic or neutral compounds . Overall, these results suggest that root tissues may accumulate high levels of anionic compounds, while in leaf tissues, cationic and neutral compounds may be more prevalent. A few other studies have considered some of these same PPCP/EDCs under hydroponic conditions, but often used higher spiking concentrations. Herkltoz et al. investigated the growth of cabbage in solution spiked with carbamazepine, sulfamethoxazole, and trimethoprim at 232.5 µg/L and found BCF values of 0.045 – 0.081 in leaf tissues and 7.04 – 10.92 in root tissues, values similar to this study for sulfamethoxazole and carbamazepine in root , but lower than carbamazepine accumulation in leaves or trimethoprim accumulation . In another study, Zhang et al. measured the uptake of clofibric acid by Scirpus validus from a culture spiked at 0.5 – 2 mg/L, and observed wetweight BCFs of 9.5 – 32.1 in leaf tissues and 6.6 – 23.2 in root tissues. These values were similar to the uptake of clofibric acid in this study . Wu et al. examined many of the same compounds at similar concentrations in nutrient solution growing cucumber, lettuce, pepper, or spinach under greenhouse conditions and observed similar BCF values in leaf and root tissues. The different environment conditions influenced bio-concentration of the PPCP/EDCs in the test plants. The mean overall BCF in the warm-dry treatment was 33.7, which was greater than that in the cool-humid treatment , although the difference was not statistically significant , likely due to the large differences in plant biomass and the wide range of chemicals used in this study. However, when BCFleaf was correlated to the transpired mass during the 21 d of plant growth, a positive correlation was observed for anionic, cationic, and neutral compounds . This result suggests that the mass flow of water caused by plant transpiration influenced the accumulation of PPCP/EDCs in leaves. Transpiration had the greatest impact on the leaf bio-concentration of cationic PPCP/EDCs, as shown by a model slope of 0.0067, while the effect was less for neutral PPCP/EDCs and much less for anionic PPCP/EDCs, suggesting that increased transpiration will have the greatest effect on leaf uptake of cationic compounds and little effect on leaf uptake of anionic compounds. This result is somewhat different than that seen for the removal of PPCP/EDCs from the nutrient solution. The difference may be attributed to other factors in addition to plant uptake, including microbial degradation in the nutrient solution.

In contrast, a relationship between BCFroot and transpired mass was only observed for the neutral group . High residuals in the linear model analysis further suggested that other factors, such as plant species, metabolism after uptake, and likely other compound properties, may also be important in describing PPCP/EDC accumulation into plant tissues. For anionic compounds, it is known that the negative charged molecules may experience repulsion from negatively charged root cell membranes, and that plant accumulation of anions may be mainly due to diffusion of the neutral fraction through the membrane and ion trap effects . A comparison of BCF values of anionic compounds in all plants with their respective log Dow showed a negative correlation for BCF leaf or BCF root , suggesting that anionic compounds with lower effective hydrophobicity had higher accumulation in the leaf or root tissues . This effect was greatest for root tissues, and the slope of the linearized regression was -54, while for leaf tissues the slope was only -0.63, suggesting other factors besides hydrophobicity may have a larger impact on the aerial uptake of anionic compounds. The cationic fraction of a compound may slowly diffuse through plant membranes due to electrical attraction between the positively charged molecules and the negatively charged cell membrane, while the neutral fraction may diffuse with preference to compounds of moderate hydrophobicity . In this study, a positive correlation was observed between BCF leaf and log Dow for cationic PPCP/EDCs in all plants , suggesting that more hydrophobic cationic PPCP/EDCs have a higher accumulation potential in leaf tissues. Further, this effect was relatively strong, with a slope of 10 for the linear regression, as compared to a slope of 6.6 for neutral compounds or -0.63 for anionic compounds. It has been shown that the accumulation of cationic organic compounds in aerial tissues was the greatest for compounds with log Kow between 2.5 –5.5 . In this study, for example, uptake of dilantin into the leaves was greater than that of trimethoprim . In comparison, no significant correlation was observed between BCFroot and log Dow for cationic compounds , suggesting that other factors also contributed to the accumulation of cationic compounds in roots. However, it must be stated again that the limited pool of cationic compounds in this study hampered a more conclusive examination of cationic PPCP/EDCs and that the assumption merits further validation.

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The effect of this cumulative dose of multiple PPCP/EDCs is unknown

For instance, the half-lives of triclosan and estrone increased from 5.9 d to 8.9 d and from 0.6 d to 1.1 d, respectively, in soils previously exposed to WWTP effluent as compared to unexposed soils . Extensive microbial transformation results in the mineralization of PPCP/EDCs in soil to CO2 and hence complete decontamination. Mineralization is exclusively mediated by microbial transformations . For example, in 3 soils, 14C-estrone showed 15 – 85% mineralization after 100 d of incubation . About 15% of 14C-bisphenol A was mineralized after aerobic incubation in 4 soils for 120 d , while only 0.49 – 0.58%of sarafloxacin was mineralized after 80 d of aerobic incubation in 3 soils . After 27 d, 50% of 14C-naproxen was mineralized . This variability shows that mineralization is compound and soil specific, similar to other microbial transformation processes. However, at present there is a general scarcity of information, making it difficult to predict the relative impact of mineralization in the overall fate and risk of PPCP/EDCs in the soil-plant-human continuum. Microbial transformations may produce many intermediate products before the compound is fully mineralized or bound in soil. The formation of transformation intermediates in soil poses unknown risks as the new products may have biological activity . Due to analytical challenges in identifying unknown products in environmental matrices, very little information on transformation intermediates is available for PPCP/EDCs . A study showed that diclofenac was transformed to 5-hydroxydiclofenac and its p-benzoquinone imine in a bioreactor with river sediment, though the levels were not quantified . While the p-benzoquinone imine was formed transiently and in small quantities, it is the known to have high hepatoxic potential . In a separate study using an activated sludge bioreactor, 7 transformation products of diclofenac were found but none were identified . Ibuprofen formed hydroxyibuprofen in a pilot sewage plant and carboxyibuprofen in an oxic biofilm reactor . Overall, knowledge of PPCP/EDC transformation intermediates in the soil is extremely limited and warrants further investigation. The application of treated wastewater, bio-solids, or manure to land creates a potential for plants to take up PPCP/EDCs ,vertical hydroponics which may be beneficial in areas of phytoremediation, but in agricultural areas may contaminate food crops and create a possible route of human exposure through ingestion .

The few studies that have examined PPCP/EDC uptake by plants have reported accumulation by a variety of edible and non-edible plants, with accumulation varying among compounds, plant species, plant tissues, exposure concentrations, and exposure durations . While potential for plant uptake has been shown in laboratory settings, many of these experiments used artificially high concentrations that are not representative of environmental levels of PPCP/EDCs. The extent of plant accumulation in the environment has been scarcely studied. Calderón-Preciado et al. analyzed alfalfa and apple trees irrigated with water impacted by WWTP effluentand identified PPCP/EDCs in plant tissues at ng/kg – µg/kg levels, verifying that PPCP/EDCs are susceptible to plant accumulation under realistic agronomic conditions. Due to the extensive suite of PPCP/EDCs, it is not feasible to empirically measure plant uptake of each compound. Therefore, it is crucial to develop a mechanistic understanding of their accumulation to inform risk assessment. Many factors affect plant uptake of organic compounds, including compound hydrophobicity, ionization behavior, soil pH, soil organic matter, and plant transpiration . Uptake is generally a passive process, occurring by diffusion that is driven by water potential gradients . Due to transpiration driving the translocation of water through the plant, compounds which are neutral, polar, persistent, and non-volatile have the potential to concentrate in plants up to 100 times the concentration in soil . Most PPCP/EDCs are non-volatile , making this accumulation pathway relevant for some PPCP/EDCs. Ionic compounds, like phenoxy acid herbicides, have the possibility to be taken up by active transport, perhaps through processes designed for uptake of essential nutrients , and may reach higher concentrations than would be expected through passive diffusion . Since some PPCP/EDCs exist primarily in an ionic state , these compounds may potentially accumulate to high levels in plant tissues. The pH of the soil-water or hydroponic solution affects the fraction of ionizable compounds that is in the ionic form. For compounds that are partly ionized at environmental pH levels, basic compounds have increased uptake and acidic compounds have reduced uptake as pH increases , due to changes in the prevalence of the neutral fraction and ion-trapping effects as discussed below.

Accumulation in plant tissues is also related to the tissue composition. Hydrophobic compounds may partition to lipids, where they have the potential to accumulate. Therefore, plants with higher lipid contents may accumulate a compound to a greater degree . The partitioning of a compound to plant lipids is related to its Kow, as discussed below. In comparison, polar compounds are expected to reach equilibrium with the water present in plants and with relatively polar carbohydrates and proteins, which suggests accumulation of these compounds will likely be less extensive . No single model is currently available that accurately accounts for all of these factors , and very little validation of plant uptake models has been done for PPCP/EDCs.Compounds may be taken up by plants when plant roots reach contaminated areas and by mass flow or diffusion of dissolved compounds to roots . Entry is typically by diffusion of neutral compounds across the root membrane, and for ionizable compounds by a combination of diffusion of the neutral fraction and electrostatic interactions by the ionic fraction . A positive relationship has been shown between hydrophobicity and root uptake of neutral pesticides and other neutral compounds . The partitioning of neutral compounds to plant lipids is very similar to the partitioning to octanol, and thus uptake models use log Kow values with adjustments for other factors, including the amount of lipids in the tissue . Based on the partitioning behaviors of neutral compounds and that 1% of barley roots were lipids, Chiou et al. predicted that accumulation into root lipids compared to the rest of the root tissue accounted for 15% of uptake for compounds with log Kow ≤ 1, but ~100% of compounds with log Kow of > 3,hydroponic vertical farming systems showing that while lipids make up a very small part of plant tissue, they greatly affect accumulation behavior and may explain some uptake differences among plant species . For neutral compounds, root uptake is expected to be the greatest for compounds with high hydrophobicity and for plants with high lipid content . Models developed for neutral compounds may be inappropriate to describe the behavior of ionizable compounds, which includes many PPCP/EDCs. The accumulation of compounds in aerial tissue can occur via deposition from volatilized compounds, direct contact with irrigation or amendment materials, and translocation from root tissues . Since most PPCP/EDCs are polar and nonvolatile, volatilization and deposition is expected to be a very minor input for aerial tissue uptake . The extent of organic compound uptake by direct contact is not very well characterized and warrants further investigation. In general, it is expected to proceed by diffusion similar to root uptake. Most studies have focused on the translocation of PPCP/EDCs from roots, which is likely to become more important than direct contact with increased use of drip and other water-conserving irrigation methods that reduce the likelihood of direct contact between plant leaves and irrigation water. Aerial accumulation of neutral organic contaminants from root tissue involves movement of compounds into xylem and then translocation to aerial parts.

Concentrations in xylem are lower than root concentrations due to hydrophobic partitioning to root tissues, suggesting that hydrophobic compounds will be predominantly retained by roots while a greater portion of hydrophilic compounds will move to xylem and be translocated to aerial tissues . Accumulation in aerial tissue competes with compound return to roots tissues via phloem, and occurs by hydrophobic partitioning of compounds to lignin, which usually has much greater affinity for organic chemicals than carbohydrates or cellulose do . Overall, studies suggest that the maximum leaf uptake of neutral compounds may occur at log Kow values in the range of 1.8 – 3.08 . However, many of these studies utilized hydroponic systems, and it has been suggested that in a soil-plant system where uptake is in competition with soil sorption, that the optimal log Kow value would be closer to 0.75 for soil with 6% organic matter,1.25 for 1.25%, and 2 for 0.25% . Similar to root uptake, aerial uptake of ionizable PPCP/EDCs is a combination of neutral fraction uptake, which can be described with log Dow values, and ionic fraction uptake, which is controlled by electrical interactions. Anions are repulsed from all cell membranes except the tonoplast of vacuoles in root cells, so uptake of anionic PPCP/EDCs by xylem and aerial tissue is predicted to be small, except in cases of ion trapping . Cations are electrically attracted to most cell membranes, enhancing diffusion to many plant parts and resulting in generally moderate uptake ability, which may be further enhanced in alkaline soils by ion trap effect . After PPCP/EDCs have been taken up into plant tissues, a number of biological processes may occur that will reduce the bio-available fraction of the parent PPCP/EDC. Xenobiotics in general are quickly modified in a plant cell by enzymes, such as hydrolases or cytochrome p450, to enable conjugation with glutathione or glucose . The conjugated compounds may then be catabolized, creating a variety of transformation products, which are eventually mineralized or incorporated into the plant tissue . The pathways andrates of these metabolic processes are likely specific to each compound and plant species . As organic contaminants, PPCP/EDCs may be metabolized in plants to form transformation products and non-extractable residue, but this area needs further research. In one of the few studies available, Bokern and Harms used cell suspension cultures to identify toxicity and metabolism of 14C-nonylphenol. Plant species which were resistant to toxicity were most efficient at incorporating the compound into cell walls, primarily associated with lignin but also with pectin and hemicellulose. Extractable polar metabolites were also detected, showing that plant cells metabolized the nonylphenol into transformation products and non-extractable residue. In another study, Macherius et al. incubated carrot cell cultures and whole carrots with triclosan, methyl triclosan, and triclocarban. Triclosan was taken up and converted to 8 different conjugated compounds in cells due to bonding at its phenol moiety, but triclocarban and methyl triclosan were found to be taken up and not metabolized. These results suggest that metabolism of PPCP/EDCs in plant may vary widely with the compound, and some compounds may exist principally in their original form in plant tissue. This area needs more research due to its human health implications. Due to the scarcity of information about PPCP/EDC accumulation in edible plants, especially for real environmental situations, the potential of PPCP/EDC residue to have a biological effect in humans is unknown. Matamoros et al. predicted that human consumption of vegetable crops irrigated with water containing PPCP/EDCs would cause an exposure of 500 ng/d of each compound, a level well below the therapeutic dose for individual pharmaceuticals but in an active range for EDCs. Based on the accumulation in radish and ryegrass grown in soil with 0.4 – 19 µg/kg of carbamazepine, diclofenac, fluoxetine, propranolol, and triclosan, Carter et al. calculated that humans might consume 0.01 – 0.21% of an acceptable daily intake for each compound in root vegetables and 0.09 – 3.81% for leaf vegetables. The major exception in the study was the high accumulation of triclosan, which was predicted to reach 83.8% of ADI in leaf tissues, nearing the acceptable limit. These studies focused on the extractable parent compound measured in laboratory uptake studies. As discussed above, it is likely that a large portion of the accumulated PPCP/EDC may be in the form of transformation products, conjugated compounds, and non-extractable residue. While non-extractable residues of xenobiotics have significantly reduced biological activity in plants and appear to be primarily not bio-available to animal metabolism, conjugated compounds may be cleaved during animal metabolism andpotentially exert toxic effects . The presence of conjugated and transformed PPCP/EDCs in plant tissue is poorly understood and the health risks from them are far from clear. Pharmaceuticals and other anthropogenic chemicals are increasingly used around the world .

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The rate of methylation or demethylation appeared to be molecule -specific

Biologically mediated transformations such as methylation and demethylation may also occur in organisms such as D. magna after their uptake of CECs, which may further influence their toxicity. Methylation and demethylation in D. magna were investigated after exposing D. magna to the individual compounds. Methylation of the selected demethylated CECs was negligible, as no methylated product was detected in D. magna after its exposure to the corresponding demethylated counterpart. However, demethylation of diazepam, methylparaben and naproxen in D. magna was evident , while acetaminophen was not detected in D. magna exposed to Macetaminophen. The demethylation of methylparaben was limited, with a peak concentration of DM-methylparaben at 0.5 ± 0.0 nmol g -1 in D. magna after 12 h of exposure to 1 mg L-1 methylparaben. This represented only about 2.0% of the molar equivalent of methylparaben in D. magna. The demethylation of diazepam was found at similar levels, with DM-diazepam at 4.4% molar equivalent of diazepam. Interestingly, the molar equivalents of the demethylated derivatives increased over time during the depuration phase, even though the overall concentrations generally decreased over time. For example, the molar equivalents of DM-diazepam and DM-methylparaben reached 33.5% and 54.8% at the end of depuration, respectively. This may be attributed to the fact that demethylation continued during the depuration phase, which may have influenced the apparent depuration of these compounds .The demethylation of naproxen in D. magna was the most pronounced among the four methylated compounds,vertical garden growing with DM-naproxen generally detected at levels higher than naproxen itself during both the uptake and depuration phases . DM-naproxen was formed quickly in D. magna after exposure to naproxen, with 21.5 ± 2.7 nmol g-1 after 12 h into the uptake phase, which was significantly higher than that of the parent naproxen .

Similar to DM-diazepam and DMmethylparaben, the molar equivalent of DM-naproxen also continued to increase during the depuration phase. At the end of depuration, DM-naproxen accounted for approximately 88.9% of the total naproxen and DM-naproxen residues in D. magna. The high proportion of DM-naproxen in D. magna also suggested that demethylation was the primary metabolism pathway of naproxen in D. magna. To better understand the demethylation of CECs in D. magna, the formation rates of DM-diazepam, DM-methylparaben and DM-naproxen were estimated by simulating their formation over the initial 12-h period, during which good linear relationships between their formation and time were present . Formation rates showed no significant differences between DM-diazepam and DM-methylparaben. However, the formation rate of DM-naproxen was significantly greater than DM-diazepam or DM-methylparaben. Based on their respective chemical structure , the demethylation of diazepam and naproxen appears to differ slightly from that of methylparaben. While the demethylation of methylparaben involves the removal of a methyl group from a carboxyl group, which may be catalyzed bycarboxylesterases,CYP450s,or through non-enzymatic hydrolysis,the demethylation of M-acetaminophen, diazepam and naproxen reflects the removal of a methyl group from an amide or hydroxyl group, which likely is catalyzed mainly by CYP450s.Previous studies showed that carboxylesterases play a more important role in drug metabolism in invertebrates due to the lower activity of CYP450s.The more significant demethylation observed for naproxen in comparison to methylparaben suggests that CYP450s may also play an important role in the metabolism of such substrates in aquatic invertebrates. The observed significant differences in the demethylation rates of diazepam and naproxen imply that CYP450s in aquatic invertebrates like D. magna may exhibit different levels of activity towards different CECs.In vivo half-lives of the test compounds were derived from the depuration rate during the 24-h depuration phase in D. magna. The in silico half-life was estimated from the primary bio-transformation rate in fish and normalized to a 10 g fish at 15 °C based on the inherent characteristics of the QSAR model.

Similar to BCF values, in vivo and in silico half-lives could not be compared directly between the different organisms. Hence, the relative persistence of test compounds was calculated for evaluation. As shown in Table 2, in silico predictions suggest that methylation may prolong the persistence of CECs in fish. This was in contrast to the in vivo results in D. magna, which showed that methylation generally shortened the persistence of CECs. As mentioned above, methylated CECs generally accumulated faster with a larger ku value during the uptake phase, but dissipated rapidly during the depuration process. Considering that biota residing in wastewater effluent-dominated streams often experience pseudo-persistent exposure to CECs due to the constant discharge of effluents from WWTPs, uptake rates may be more important in regulating the accumulation of CECs in aquatic organisms dwelling in the impacted system. The prolonged bio-transformation half-lives of methylated CECs should be validated under field conditions. Overall, in silico predictions and experimental measurements were in agreement for the influences introduced by methylation or demethylation. This highlights the feasibility of incorporating QSAR models to evaluate the potential influence of common transformations such as methylation and demethylation on the environmental risks of CECs to non-target organisms in impacted ecosystems. Simple transformations such as methylation and demethylation contribute to the proliferation of the numbers of CECs and diverse structures in environmental compartments impacted by e.g., wastewater effluent.This study showed that these transformations can alter the physicochemical properties of CECs, resulting in changes in their environmental processes such as bio-accumulation and acute toxicity in aquatic organisms. These transformations of man-made chemicals may also take place within a non-target organism after their accumulation from the ambient environment.

Certain transformations, like methylation, likely result in enhanced bio-accumulation and increased toxicity in non-target organisms. Although not considered in this study, halogenation of man-made chemicals, such as gemfibrozil, 4-nonylphenol and naproxen, during the disinfection process in WWTPs, has also been reported, and the halogenated products generally exhibited increased bio-accumulation and toxicity to aquatic invertebrates.Due to the presence of numerous CECs in sources such as wastewater effluents and sediments, the co-existence of various TPs presents an additional challenge in addressing the overall environmental risks of man-made chemicals. It is important to note that high concentrations of test CECs and their corresponding methylated or demethylated TPs were used in this study in order to derive the LC50values and examine conversions in D. magna; these concentrations were above environmentally relevant levels. However, previous studies suggested that BCFs may be greater at lower exposure concentrations.Therefore, the effect of methylation or demethylation on bio-accumulation of CECs may be more pronounced than what was observed in this study. The environmental occurrence and concentrations of methylated or demethylated TPs are largely unknown for most CECs. Further research into the occurrence of TPs in different environmental compartments is needed to gain knowledge about the realistic exposure levels and to refine risk assessment. A major challenge in comprehensively assessing environmental risks is the sheer number of CECs and their TPs. It is unrealistic to experimentally evaluate transformation-induced changes in their environmental behaviors and toxicological profiles for all CECs.The incorporation of well-established QSAR models to predict essential chemical properties and environmental risk markers, such as hydrophobicity and lipophilicity, bio-accumulation potential, and acute toxicity, may help prioritize TPs with enhanced biological activities.This approach can be used to more effectively direct future research efforts to better understand the environmental significance of common transformation reactions for CECs. Four CECs and their methylated or demethylated TPs were comparatively evaluated for their uptake into A. thaliana cells or by wheat seedlings. The methylated compounds, generally more hydrophobic with a greater log Kow and log Dow,equipment for vertical farming often displayed a greater accumulation potential in both plant models as compared to their demethylated counterparts, with the exception of acetaminophen/M-acetaminophen in A. thaliana cells. The influence of methylation and demethylation on the translocation of CECs in wheat plants was molecular-specific. Methylation caused a significant increase in the translocation of acetaminophen, but a significant decrease for DM-diazepam. Methylation also generally prolonged the persistence of CECs in both A. thaliana cell culture media and wheat seedling hydroponic solution. A significant linear relationship was observed between log Dow and log BCF, indicating that the generally increased accumulation of methylated compounds may be attributed to their higher hydrophobicity. Results from this study suggested that common transformations such as methylation and demethylation may affect the persistence and accumulation of CECs in plants, and their role should be considered to obtain a more comprehensive understanding of the risks of CECs in the terrestrial environment including agro-food systems.

The interconversions between CECs and their methylated or demethylated TPs were evaluated in A. thaliana cells and wheat seedlings after their uptake. The methylation demethylation cycle was observed in both plant models, with demethylation generally taking place at a greater degree than methylation. Computation results showed that the chemical bond strength between the methyl group and the major molecular fragment in the methylated CECs followed a general order of methylparaben < diazepam < naproxen < M-acetaminophen, a pattern reflective of experimental observations for demethylation in A. thaliana cells. Future studies considering more chemical structures would help strengthen such QSAR models so that the potential for simple transformations such as methylation and demethylation may be predicted in the absence of experimental data. The acute toxicity of selected CECs and their methylated or demethylated TPs was further assessed by exposing D. magna to individually compounds. Methylation or demethylation resulted in changes in the acute toxicity for most CECs, and the influence was compound-specific. Methylation led to a significant increase in the acute toxicity of DM-methylparaben and DM-naproxen, but a decrease for acetaminophen. A significant negative linear relationship was observed between log LC50 values and log Dlipw values, indicating that as log Dlipw increased, the acute toxicity generally increased. Methylation increased the bio-accumulation in D. magna for acetaminophen, DM-methylparaben and DM-naproxen, and the increased bio-accumulation likely underlined the increases in acute toxicity for methylated compounds. In D. magna, active demethylation of diazepam, methylparaben and naproxen was observed, with the demethylation of naproxen especially pronounced, suggesting that enzymes in D. magna exhibited different levels of activity towards different substrates. QSAR models were used to predict changes in acute toxicity and bio-accumulation as a result of methylation, and the predicted values were in good agreement with experimental observations. The exploratory research presented in this dissertation clearly showed that simple transformations such as methylation and demethylation can significantly change the physico chemical properties of CECs and subsequently cause changes in their environmental behaviors such as accumulation by plants and aquatic organisms, toxicity and persistence. Methylation generally leads to increased hydrophobicity and further greater bio-accumulation and acute toxicity. However, exceptions were also observed in this study, suggesting that specific molecular structures may respond differently to the impact of simple transformations. QSAR models using molecular descriptors have the capability to predict the easiness of transformation reactions such as methylation and demethylation, the subsequent changes in physicochemical properties from such transformations, and further, the ensuing changes in bio-accumulation, translocation, and toxicity. Such models should be calibrated with more experimental observations and by the inclusion of more diverse structures. Such predictive tools are extremely valuable, given the enormous number of CECs and their transformation products, which renders experimentation-based approaches largely infeasible. This dissertation research highlights the prevalence of simple transformations such as methylation and demethylation in the environment, and the need to consider such transformations in achieving a more comprehensive understanding of the environmental fate and risks of CECs.Results from this dissertation research and a few other studies showed that simple transformations can effectively influence the environmental behaviors of CECs, and the effect is specific to molecular structures. Changes in bio-accumulation and toxicity due to transformations should be further evaluated under environmentally relevant conditions. The greatest challenge to understanding the environmental risks of CECs is the sheer number of CECs and their metabolites. In the absence of experimental data, predictive tools such as QSAR models and computational chemistry should be used to predict the possibility for the occurrence of transformations as well as the changes in physicochemical properties accompanying these transformations. Likewise, modeling may be also used to estimate changes in environmental behaviors and risks for CECs that are susceptible to transformations. It must be noted that only methylation and demethylation were considered in this research.

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These chemicals are known to have adverse effects on non-target aquatic organisms

Glycosylation was observed for diclofenac, sulfamethoxazole and di-n-butyl phthalate in A. thaliana, triclosan, naproxen, diclofenac, ibuprofen and gemfibrozil in carrot cell cultures,bisphenol A and carbamazepine in lettuce,and TBBPA in pumpkin seedlings.Acetaminophen and chlortetracycline were conjugated with glutathione in cucumber seedlings and maize seedlings, respectively.Conjugation with other biomolecules, such as saccharides, malonic acid, and sulfate, was also occasionally reported for some CECs, such as triclosan in carrot cells and diclofenac in A. thaliana cells.Other than conjugation, methylation is also a type of phase II metabolism and has been reported for TBBPA in pumpkin seedlings. The investigation of phase III metabolism of CECs in plants is relatively limited, as quantitative evaluation of phase III products would require the use of isotope labeling to account for the nonextractable or bound residues, although phase III is expected to be dominant in determining the final destination of xenobiotics in plants. For instance, nearly all 14C- labeled naproxen, diclofenac, bisphenol A and nonylphenol were found in nonextractable bound residues in lettuce and collards.Numerous studies have documented the occurrence of CECs in aquatic environments in many countries and regions. CECs are introduced into aquatic environments via discharge of TWW from WWTPs, agricultural activity, landfill leachates, and surface runoff . Concentrations of CECs ranges from ng L-1 to μg L-1 in impacted surface water and from μg kg-1 to mg kg-1 in the sediment. The concentration of CECs in surface water is largely influenced by the population density, environmental conditions and terrigenous supply, displaying temporal and spatial variations. Studies conducted in the U.S. in recent decades have shown the occurrence of hundreds of CECs in various watersheds, with the maximum concentration at 35 μg L-1 for sucralose in water. A comprehensive review of the occurrence of CECs in Latin America, including studies performed in 11 different countries between 1999 and 2018,vertical planters for vegetables has shown the common detection of 17β-estradiol, bisphenol A and estrone.

The highest concentration of CECs detected reached 1100 μg L-1 for clindamycin in Costa Rica.Many survey studies have also been reported for countries in Europe, such as the Sava River in Slovenian and Croatian,rivers receiving TWW in Ireland,and impacted rivers and lakes inSweden.An EU-wide survey of CECs in European river waters indicated that benzotriazole, caffeine, carbamazepine, tolyltriazole, and nonylphenoxy acetic acid were among the most frequently detected and/or at the highest concentrations.In addition, levels of CECs in some developing countries may be higher than those in developed countries, likely due to less rigorous treatment at WWTPs. For example, naproxen as high as 140 μg L-1 was reported in a study originated in India and up to 167 μg L-1 for lamivudine in Kenya.Research focusing on the occurrence of CECs in sediment is less prevalent and typically involves fewer CECs. Furthermore, the concentration of CECs in sediments usually exhibits less seasonal variations, which suggests that sediment samples may serve as a more stable marker for CEC monitoring in aquatic environments.High detection frequencies and concentrations of estrone and 17β-estradiol have been reported in sediments from the mouth of the Manokin River in the U.S., with the highest concentration at 58.4 μg kg-1 and 11.5 μg kg-1 , respectively.In the Southern California Bight, triclosan, 4-nonylphenol and bis have been detected in all sediments at median concentrations of 5.1 , 30 , and 121 μg kg-1 , respectively.The highest total concentration of antibiotics in sediments from the intertidal zones of the Yellow River Delta, China was measured to be 178.77 μg kg-1 . 124 Studies conducted in African countries such as Morocco showed even greater CEC concentrations in the sediment . Interestingly, several surveys have shown the presence of some hydrophilic CECs in sediments, such as acetaminophen and caffeine, which were previously thought to have limited sorption to solids due to their low hydrophobicity.Aquatic organisms living in impacted aquatic environments have been sampled for detection of CECs. CECs have been found in the tissues of fish, mussels and oysters collected from the impacted water systems in the U.S., with the maximum concentration detected at 3000 ng g-1 for 4-nonylphenol in mussels, suggesting potential bioaccumulation of CECs in aquatic organisms.

Diazepam was detected in all collected flatfish liver samples in Southern California but was infrequently detected in sediments, highlighting the bio-magnification potential of certain CECs.The accumulation of PBDEs in fish livers was comparable to that of legacy organochlorines.Water snakes and small common carps living in an e-waste contaminated water pond were reported to accumulate plasticizers and organophosphorus flame retardants in their tissues.Therefore, aquatic organisms may be exposed to low levels of CEC mixtures in the environment, and bio-accumulation in aquatic organisms is possible for some CECs. As CECs are continuously introduced into aquatic environments via various pathways, they may be considered as pseudo-persistent contaminants, causing long-term, mixed, low-dose exposure to aquatic organisms. A comprehensive review of the ecotoxicity of human pharmaceuticals concluded that for all human medicines tested, acute effects to aquatic organisms were unlikely, unless spill incidents occurred, due to their trace level occurrence in aquatic environment.The chronic lowest observed effect concentrations of most tested pharmaceuticals in standard laboratory organisms are about two orders of magnitude higher than what detected in the effluents.However, recent studies showed that some CECs may exert unintended adverse effects to organisms, such as endocrine disruption and developmental toxicity, at environmentally relevant levels.The investigation on toxic effects of CECs on aquatic organisms includes two main types of exposure: direct exposure to the real environment, such as TWW and impacted water, and exposure to water spiked with CECs under controlled conditions. Chronic effects, including sublethal effects, have been often observed in aquatic organisms exposed to affected water bodies or TWW. For example, fathead minnows and freshwater mussels were caged for 4 weeks upstream and downstream of the discharge from WWTPs, and were found to develop multiple biomarker responses, such as oxidative stress, enzyme induction, shifts in gene expression and alteration of immune functions.

The growth and yield of green algae and reproduction of daphnia were inhibited by TWW and exhibited dose-response effects. Juvenile rainbow trout exposed to TWW showed significantly different plasma cortisol and glucose response to the secondary stressor.However, it is often difficult to interpret the impact of CECs in this type of experiments, as various other stressors, such as water temperature and bacteria in the real environment, may also induce such biomarker responses.The low concentrations of CECs in TWW also could not explain the sublethal effects observed on algae and daphnia.In addition, interactions of compounds in CEC mixtures should be further considered. The exposure of aquatic organisms to artificially spiked CECs, on the other hand, provides comparable toxicological data under controlled conditions. Most research has been devoted to the toxic effects of CECs at the individual level, while in realistic situations, CECs are always present as a mixture. Exposure to CECs at environmental relevant levels cause multiple adverse effects. For example, marine mussels exposed to atorvastatin at around 1.2 μg L-1 exhibited key fatty acid metabolism disruption and suppression of xenobiotics efflux through P-glycoprotein and membrane diffusion.Gemfibrozil was shown to reduce plasma androgens in goldfish after exposure to 1.5 μg L -1 for 4 and 14 days;while the concentration of gemfibrozil in WWTP effluent was found to be in the range of 10-3830 ng L-1 . The adverse effects of CECs have also been shown at the population level. For example, a 7-year, whole lake experiment conducted in northwestern Ontario, Canada, showed that chronic exposure of fathead minnow to 5-6 ng L-1 of the synthetic estrogen, 17 α- ethynylestradiol,vertical farming technology led to the near extinction of this species.Aquatic invertebrates have been widely adopted to derive acute toxicity end-points, e.g., LC50 values, for target CECs. The acute toxicity of CECs varied greatly, even for compounds belonging to the same chemical class and displayed species-specific effects. For example, the EC50 and LC50 values varied largely among the 12 tested polychlorinated diphenyl ethers for S. obliquus, D. magna, and D. rerio, respectively.Exposure to 17α-ethinylestradiol, acetylsalicylic acid, and bisphenol A significantly affected the embryonic development of sea urchins, with different LC50 values for Mysidopsis juniae and Artemia sp. The concentrations that induced 50% growth inhibition in algae of metolachlor, erythromycin, and triclosan also showed multiple-fold differences between freshwater and marine algae, reflecting the species-specific sensitivity.Mixed exposure of silver nanoparticles, polystyrene nanoplastics and 5-fluorouracil displayed interaction toxicity to marine mussels, with exponentially increased oxidative damage compared to individual contaminants,highlighting the importance to consider chemical interactions when investigating the toxic effects of CECs in the real environment. Some government agencies in the U.S., such as EPA and California State Water Resources Control Board, have tried to put some regulations to control CECs in aquatic environments. For example, the Science Advisory Panel for CECs in California’s aquatic ecosystems has developed strategies to identify the monitoring trigger levels of CECs in aquatic environments based on their lowest effect values available from established databases, such as the Computational Toxicology database and the NORMAN database , for aquatic organisms.However, for the TPs of CECs, such data are usually not experimentally available. Due to the huge and continually increasing number of CECs in aquatic environments, it is unrealistic to examine the toxicity effects of all CECs. Several studies have attempted to develop a prioritization process to select CECs that require the most attention for aquatic organisms based on their monitoring data, production volume, persistence and prevalence in the environment, bio-accumulation potential, and biological effects.

Several modeling tools, like machine learning and quantitative structure-activity relationships , have also been developed to predict the bio-accumulation, bio-transformation and toxicological effects of CECs.For example, Sequence Alignment to Predict Across Species Susceptibility was adopted by the Science Advisory Panel for CECs in California’s aquatic ecosystems to predict the behaviors of CECs across species without available toxicological data from the existing database.The incorporation of such tools is of vital importance to improve risk assessment of CECs due to the limited experimental resources. Studies have often revealed that TPs of CECs occur simultaneously in the tissues of aquatic organisms with their parent compounds, sometimes at even higher concentrations. For instance, metabolites of organophosphorus flame retardants were found in the same order of magnitude as their parent compounds in water snake and small common carps collected from an e-waste-affected site. Norsertraline, the demethylated TP of sertraline, was found to be bio-accumulated at a greater degree than sertraline in the liver of rudd collected from the TWW-impacted Niagara River.Nordiazepam, the demethylated TP of diazepam, was also frequently detected in aquatic organisms along with diazepam.127 Therefore, TPs of CECs in aquatic organisms could originate from two sources – uptake from the ambient environment, and transformation taking place in the organism upon the uptake of the parent compound. Research focusing on the biotransformation of CECs in aquatic organisms, including aquatic plants such as algae, invertebrates such as daphnia, and vertebrates such as fish, is limited. However, the identification of CEC metabolites in aquatic organisms is crucial for evaluating the ecological risks of CECs. Prevalent phase I and phase II enzyme activities were frequently induced in aquatic organisms after CEC exposure, such as cytochrome P450 enzymes and glutathione transferases.Although some common metabolites might be expected, the pattern of CEC metabolism could also vary between different species. For example, three phase I metabolites and 10 phase II metabolites were identified in marine mussels exposed to diclofenac,while 7 phase I metabolites and 3 phase II metabolites were found in H. Azteca and G. pulex. Significant differences in biotransformation rates were observed for different species or between opposite sexes of fishes exposed to CECs.157 Certain aquatic species, such as glass eels, displayed low metabolic activity, with few metabolites detected after CEC exposure,155 while the absence of bio-magnification effects of PFRs in water snakes was attributed to the active bio-transformation. Bio-transformation of CECs in algae shared some similar pathways as that in terrestrial plants, as in the case of hydroxylation, demethylation and glycosylation of bisphenols.Methylation and demethylation are common transformation pathways for chemicals in the environment, especially for compounds with -OCH3, -NCH3-, -SCH3, and/or the corresponding -OH, -NH-, and -SH groups in their chemical structures.

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Flag leaves were harvested from plants four days after panicle emergence

To use the SPQV, all QTL with a sufficiently high logarithm of the odds score should be assessed. The function provides the higher and lower confidence limits, as well as the combined CI for each mathematically related set of QTL. If any QTL within a set exceeds the combined CI for that set, then the whole set can be deemed successful. QTL with observed gene counts that exceed the upper confidence limits should of course be considered to have attained significance. If at least one QTL in an experiment is determined to be significant by the SPQV, the mapping experiment on a whole can be deemed a success. The QTL that contain lower numbers of genes might be identifying previously unknown genes, and therefore their non-significance does not detract from the significance of other QTL. Because of the potential for the identification of new phenotype associated genes in QTL mapping, QTL containing significantly low numbers of identified genes might also be of interest, as they may have been placed on ’empty’ regions due to previously unidentified genes that have a large impact on the phenotype. The QTL containing significantly low numbers of genes should only be considered interesting when at least one other QTL in the same mapping experiment has been proven to be significant so as to avoid the suggestion that all QTL in a faulty mapping study were significant. The intake, transportation, and storage of elements within a plant is vital to its appropriate growth and development. Plants must maintain balance between excessive uptake, which can cause toxicity and necrosis through the production of free radicals or the exclusion of other nutrients, and sufficient uptake of essential inorganic nutrients . Tight control of ion homeostasis allows plants to respond appropriately to environmental conditions such as temperature, soil pH, and water availability . This regulatory control must be responsive to both the concentration of ions within the soil and to those concentrations within the plant. Understanding the genetic control of elemental uptake and transportation will contribute to efforts to improve crops,vertical farming tower for sale and to the ultimate sustenance of the growing global population.

Examining the concentration of elements within a plant sample allows for exploration of the genetic and physiological processes involved in adaptation to a particular environment. To this end, we and others have developed a pipeline that is designed to cheaply and efficiently measure the concentrations of 20 different elements via inductively coupled mass spectrometry . This process is known as ionomics, which is defined as the quantitative study of the mineral nutrient and trace elemental content of an organism; that is to say, its ionome . In cereal crops such as Setaria italica, the flag leaf emerges just before the panicle, and therefore marks the specific developmental time point at which the plant has taken up the majority of its total mass. This tissue is therefore ideal for ionomic inquiry. Additionally, nutrient loading of the grain is accomplished through the remobilization of organic and inorganic materials from the leaves . The flag leaf specifically is instrumental in the loading of photo assimilates and other micro-nutrients , and is therefore commonly used as representative tissue to assess the composition of a grass . The species Setaria viridis, or green foxtail millet, is a member of the Panicoideae that utilizes C4 photosynthesis . It is therefore a good model system for several related, economically important crops, including sorghum and maize. The compact stature, short life span, and sequenced genome of S. viridis have also contributed to its status as an emerging model organism . In addition, S. viridis is the wild ancestor of the crop species Setaria italica ; these two species have a semi-permeable boundary between them, as their primary difference is phenotypic and they are still readily crossed . Foxtail millet is a member of the small millet species, a group of ancient grains that are relatively nutritionally dense when compared to rice and wheat and which are often cultivated as subsistence crops . Because of the combination of the high nutritional value of the S. italica grain and its resistance to abiotic and biotic stressors, breeding elite cultivars of S. italica for increased nutritional content is an attractive prospect. Understanding the contribution that different regions of the S. italica genome make to total nutrient content is an important first step for breeding purposes.

Structured populations are useful tools for dissecting the relationship between elemental accumulation and the genetic content of a species. Recombinant inbred lines have various advantages when it comes to quantitative trait loci analyses. Repetitive selfing allows for the break up of large linkage blocks, which in turn allows for finer mapping . Additionally, once established, RILs may be continuously maintained in a fixed homozygous state. This makes it possible to assay the same combinations of alleles in multiple different environments . The resulting phenotypic and genotypic data can then be compared through various statistical means in order to identify QTL. Here, we use elemental profiling of a RIL population resulting from a wide cross between S. italica and S. viridis grown in multiple environmental conditions to identify QTL associated with the ionic content of leaf material. Overall, we identified 251 QTL, 171 of which were associated with a single element and 80 of which were associated with a principal components analysis of the ionome. The use of traits defined by the differences between treatments in an experiment allowed for the quantification of the influence of the environment on Setaria’s ionome. Experiments were conducted in the summers of 2013 and 2014. Experiments assaying the effect of density of planting on ionic content were conducted in 2013 and 2014. A single drought experiment was conducted in 2014. A total of 189 F7 RILs resulting from a wide cross between the B100 cultivar of S. italica and the A10 line of S. viridis, together with their parent lines, were used as the study material . In every experiment, lines were planted in triplicate in a block design in the field in Creve Coeur, MO. Treatments in the density experiment consisted of either five centimeter spacing between neighboring plants, or twenty centimeter spacing between neighbors. Plants in the drought experiment were either well watered until the time of sample collection, or were subjected to drought stress from eight weeks post planting. The data used for this work included measurements for 20 different elements in flag leaf tissue collected from a recombinant inbred line population resulting from the cross of the B100 cultivar of Setaria italica and the A10 line of Setaria viridis. A drought experiment was conducted in Creve Coeur, Missouri in 2013 ; both a drought and a density experiment were conducted in the same location 2014 . 179 of the RILs were planted in at least two of the three experiments, while 116 were grown in all three.

The leaf samples from all experiments were treated in an identical fashion; samples were dried and stored in temperature and humidity controlled rooms before ionomic analysis. Each sample was profiled for the quantity of 20 elements using ICP–MS . The resultant measurements were normalized to the sample weight and technical sources of variation using a linear model. Experiment level analytical outliers were removed as in Davies and Gather 1993. Pursuant to this, the measured values for each element were transformed to normality using the Box Cox family of transformations, and Studentized deleted residuals were used to identify and eliminate further outliers within the measurements for each element. After outlier removal,hydroponic vertical farm phenotypes were derived by averaging the values for each line within an experiment and treatment. Both environment and genotype impacted the variation present in these data. Repeatability was generally lower than within experiment heritability , indicating that there was less variation in genotypic replicates within an individual experiment than across experiments. The broad sense heritability of 9 elements in the DN13 experiment, 14 elements in the DN14 experiment and 16 elements in the DR14 experiment exceeded 0.4. Certain elements including selenium, sulfur, and boron showed low repeatability; this is likely due to the fact that these elements tend towards analytical artifacts, as they accumulate to levels that are near the limits of detection of the methods described in this paper. The heritability of individual elements varied by up to 0.533 between different experiments. The function stepwiseqtl from the R package was used in order to identify a multiple QTL model for each of the elemental phenotypes. This function moves iteratively through the genome to test for significant allelic effects of each marker on the phenotype in question. When a significant locus has been identified, this is added to the model. A combination of forward and backward regression ultimately produces a genome wide QTL model for each trait. Each element was considered individually, as well as in combination with the others as a contributor to a principal components analysis that was run for each experiment . Five different metrics were used as the phenotype for each element in each experiment. These phenotypes include the ‘raw’ values for each treatment and the differential values for that trait .

The significance of a QTL was computed using the 95th percentile threshold resulting from 1000 iterations of the scanone function as a penalty for adding the QTL to the model. When all experiments are considered, a total of 251 QTL were identified . As expected from the heritability measurements, the majority of these were identified in the 2014 drought experiment . The 2013 and 2014 density experiments allowed for the identification of 75 and 71 QTL, respectively. Approximately a third of the QTL were identified within treatments; the remainder were identified using either the difference, relative difference, or ratio of the phenotypic values measured within the different treatments in a single experiment . Of the 251 QTL, 80 were identified for the mapping based on the principal components analysis; 39 of these resulted from the drought experiment, 21 from the 2013 density experiment, and the remaining 20 from the 2014 density experiment. Of the 251 QTL, 55 were located on chromosome 2 . The locations of the QTL were assessed for overlap with the locations of known ionic genes . Forty five of the QTL contained at least one gene within their 95% confidence intervals. Of the QTL that coincided with genes, 35 were identified using PC as the mapped trait. The QTL were assessed for significance using the Scanning Probabilistic QTL Validator. The QTL were divided into mathematically related sets based on experiment and the phenotypic metric that was used when they were mapped. The results of this assessment are reported in Table 3-3; each phenotypic metric that was used for mapping was associated with at least one set of QTL that identified a significant number of genes, indicating that the data curation was done effectively. There were several regions in which QTL were remarkably concentrated. Fifteen QTL were identified on chromosome 2 between 89.4 and 95.9 cM ; these QTL were discovered in both the 2013 density experiment and the 2014 drought experiment. The traits associated with these QTL included As, Al, Co, Cu, Mo, P, Rb, and Sr, as well as PC2 for the 2013 density experiment. In the context of the ionome, principal components analysis allows for the identification of regions of the genome that would not otherwise be found. While some of the PC QTL identified regions that overlapped with those identified by ion specific QTL, the majority of them, including many QTL identified for PCs which explained a large amount of the variance present in the data, did not. It is possible that for a single ion, the signal associated with the PC QTL regions is not sufficient for their identification, while the additive signal that is inherent in a principal component suffices. Moreover, many of the first few principal components overlay regions associated with water use efficiency , with concentrated regions of QTL identified on chromosomes 2, 5, 7, and 9 at positions 94, 111.9, 99.9, and 123.7, respectively.

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An additional experiment was carried out in an airtight container without aeration

Briefly, 400 mg sub-samples of the dried, ground plant matter were freeze-dried for 12 h, weighed, and extracted in polypropylene tubes by sequential sonication and centrifugation with 20 mL methyl tert-butyl ether and then again with 20 mL acetonitrile. The combined extracts were evaporated under nitrogen to less than 1 mL, and mixed with 5 mL methanol and 20 mL water. A 6 mL aliquot of the extract was taken for analysis by LSC to determine the fraction of activity as extractable residue. Selected 150 mg sub-samples of the solventextracted plant matter were combusted on the Biological Oxidizer as described above to determine the fraction of 14C present as non-extractable residue. When nutrient solution and jars were exchanged, the volume of remaining nutrient solution in each jar was gravimetrically determined. A 9 mL aliquot of the solution was mixed with 13 mL Ultima Gold scintillation cocktail and the 14C was quantified by LSC. Water loss from evaporation during each 3 d period was found to be negligible in the no-plant control containers. It is likely that microbial activity in the nutrient solution may have resulted in transformation of the spiked 14C-compounds and that plants may have accumulated both parent PPCP/EDCs and transformation products. To discern the contribution of transformation products to plant accumulation, the used nutrient solution from day 21 was preserved with 2 g sodium azide and 100 mg ascorbic acid, extracted, and fractionated using high performance liquid chromatography . Solutions from 14C-BPA, DCL, or NPX treatments were first filtered through a What man #4 filter paper and then passed through a HLB solid phase extraction cartridge . Before use, the cartridges were sequentially conditioned with 5 mL each of MTBE, methanol , and water. The filtered solution was drawn through the conditioned HLB cartridges under vacuum and followed by 50 mL deionized water. A sub-sample of the filtrate that passed through the cartridge was collected for analysis by LSC to quantify 14C that was not retained by the cartridge.

The cartridges were dried with nitrogen gas,hydroponic bucket and then sequentially eluted with 5 mL of MeOH:MTBE and 5 mL MeOH. The collected eluent was dried under nitrogen to 100 μL. The concentrated eluent was transferred to an HPLC vial equipped with a 250 μL insert. The condensing vial was rinsed with 130 μL of methanol, and the rinsate and 20 μL of non-labeled parent standard were added to the HPLC vial. Preliminary experiments showed that the recovery of this extraction procedure from the initial solution to HPLC analysis was 81.5 ± 7.1% for BPA, 85.8 ± 2.5% for DCL, and 74.0 ± 1.9% for NPX. Nutrient solutions from the 14C-NP treatment were extracted by a simple liquid-liquid extraction method. Each nutrient solution sample was shaken with 50 mL hexane for 30 min, and then the upper layer of the sample was transferred to a centrifuge tube and centrifuged at 3500 rpm for 30 min to reduce emulsification. The hexane phase was transferred to a 15 mL glass tube, concentrated under nitrogen to 300 μL, and transferred to an HPLC vial. The condensing vial was rinsed with 180 μL of methanol, and the rinsate and 20 μL of non-labeled NP standard were added to the HPLC vial. The recovery of this extraction method from the initial solution to HPLC analysis for NP was determined to be 66.8 ± 12.0%. Young plants of lettuce and collards were grown for 21 d in nutrient solution containing one of the four 14C-labeled PPCP/EDCs. No significant differences in plant mass were observed between treatments at the end of the experiment. During the experiment, three plants died . Figure 2 shows the mean mass balance for the systems at the end of the experiment, depicting the fractions of the spiked 14C present in plant tissues, in the used nutrient solution, and as unaccounted activity. The unaccounted activity reflected the 14C that was not found in the nutrient solution at the time of solution renewal or in the plant tissues after harvest and may include losses via unidentified processes, such as volatilization, microbial mineralization in the nutrient solution , or stomatal release. Activity in each fraction varied across compounds and to a lesser degree across plant species, suggesting specificity to uptake. Figure 3 shows the cumulative 14C dissipation from the nutrient solution as calculated from the difference in activity in the solution at the beginning and end of each 3 d interval of solution renewal, representing 14C loss from plant uptake and other processes. Dissipation followed the decreasing order of BPA > NP > DCL > NPX for all treatments and occurred at a similar rate throughout the 21 d cultivation. The presence of plants significantly increased the dissipation of PPCP/EDCs from the nutrient solution, except for NP.

For example, the initial concentration of 14C-DCL in the nutrient solution was 105.3 ± 0.3 dpm/ mL, but it decreased to only 32.8 ± 1.9 dpm/mL after 3 d in the presence of lettuce, while 91.2 ± 3.2 dpm/mL remained in the no-plant control. Lettuce and collards treatments had different levels of chemical dissipation in the nutrient solution. For example, the overall dissipation of BPA in the lettuce treatment was 69.1 ± 8.7%, as compared to 88.4 ± 5.3% in the collards treatment . Different compounds also dissipated at different rates. For instance, in the presence of collards, the cumulative loss was 88.4 ± 5% for BPA, 55.6 ± 11.8% for DCL, and 45.5 ± 4.3% for NPX.The dissipation of NP in the solutions with plants was found to be similar to that in the noplant control, especially for the lettuce treatment . The loss of NP from the noplant control was likely associated with volatilization, as continuous aeration was used to maintain the oxygen level in the nutrient solution throughout the experiment. The Henry’s Law constant for NP is 1.09 ×10−4 atm m3 mol−1 , suggesting a tendency for volatilization. The loss of NP in the solution was found to be insignificant, as all of the spiked 14C was found in the solution , and a solvent rinse of the system showed little sorption of 14C-NP on the container wall . Doucette et al. found that in a hydroponic set up, about 13% of the spiked NP was lost to volatilization in the absence of plants. The increased volatilization losses in the current study were likely due to specific aeration and temperature conditions used. Despite volatilization losses, significant amounts of 14C were detected in plant tissues, suggesting that both collards and lettuce accumulated NP . Noureddin et al. studied the uptake of 5 mg/L BPA from hydroponic solution by water convolvulus and found that approximately 75% of the spiked BPA was removed after 3 d. This removal was comparable to that observed for BPA with lettuce in this study, but was smaller than that with collards . Calderón-Preciado et al. evaluated hydroponic uptake of triclosan, hydrocinnamic acid, tonalide, ibuprofen, naproxen, and clofibric acid by lettuce and spath and showed that the removal of NPX from solution was about 70% for lettuce and 10% for spath after 3 d. In comparison, Matamoros et al. observed less than 10% removal of NPX after 3 d of hydroponic growth with wetland plants , while 46% removal of NPX was measured in the collards treatment in the present study.

Matamoros et al. also showed that DCL did not dissipate appreciably in treatments with wetland plants, which was in contrast to the high removal of DCL by leafy vegetables observed in this study . It is likely that the smaller plant mass and the use of non-aerated nutrient solution in the earlier study contributed to the limited plant uptake. The range of variation suggests that plant species,stackable planters along with other factors such as plant mass and environmental conditions, affect the actual accumulation of PPCP/ EDCs into plant tissues. Plant tissues were collected after 21 d of cultivation, rinsed with deionized water, and separated into roots, stems, new leaves, and original leaves for analysis of both extractable and non-extractable 14C. Table 1 shows concentrations of 14C in plant tissues, expressed as parent-equivalents. In agreement with the dissipation trends in solution, plant accumulation followed the decreasing order of BPA > NP > DCL > NPX. Concentrations based on dry plant mass ranged from 0.22 ± 0.03 to 12.12 ± 1.91 ng/g in leaves and stems. Statistical analysis showed that the accumulation in leaves and stems was not significantly different between lettuce and collards, or among the different compounds. In contrast, roots accumulated significantly more 14C than all the other plant tissues, with concentrations that ranged from 71.08 ± 12.12 to 926.89 ±212.89 ng/g. Accumulation of 14C in plant tissues exhibited several apparent trends. In whole collards plants, significantly greater accumulation was found for the neutral compounds BPA and NP than the anionic compounds DCL and NPX , suggesting that the charge state of PPCP/EDCs may greatly influence plant uptake . Similar effects have been frequently observed for anionic herbicides, and are attributed to exclusion of negatively charged molecules by cell membranes . Between lettuce and collards, lettuce significantly accumulated less PPCP/EDC when all test compounds were pooled , although the interaction effect for individual compounds was not significant . Accumulation of BPA or NP in plant roots was significantly higher for collards than lettuce , while portion of DCL accumulated into lettuce and collards roots was not significantly different. Analysis of tissue extracted with solvent showed that essentially all of the 14C was non-extractable; only the root samples from NP-collards treatment contained a detectable fraction of 14C in extracts .

Combustion of extracted plant tissues confirmed that almost all 14C remained as non-extractable residue, one possible endpoint for xenobiotics taken up by plants . Only a few studies have examined the plant uptake of some of the same PPCP/EDCs considered in this study. Wu et al. grew iceberg lettuce and spinach for 21 d in hydroponic solution initially spiked with a suite of 19 PPCPs, including DCL and NPX, each at 500 ng/L and found no detectable residues of DCL or NPX, except for NPX in spinach at 0.04 ng/g. Calderón-Preciado et al. analyzed apple tree leaves and alfalfa from fields irrigated with water containing BPA, DCL, and NPX. DCL was detected at 0.354 ng/g in apple leaves and 0.198 ng/g in alfalfa; NPX was detected at 0.043 ng/g and 0.04 ng/g, respectively. The low concentrations found in these studies generally agree with the findings of this study, but there is some variation in the tendency for specific compounds to accumulate. This variation may be partly attributed to the different analytical approaches. In other studies, uptake of PPCP/EDCs by plants was evaluated using non-labeled compounds, and accumulation was measured by targeted chromatographic analysis for the extractable parent compound. The use of 14C-labeled compounds in the current study should have provided “worst-case” estimates of human exposure, as the concentrations included non-extractable residue and likely also included transformation products. Transformation products may be an important component of potential risk since the metabolites of some PPCP/EDCs have higher biological activity than their parents and studies have shown that a large portion of PPCP/EDCs that are taken up by plants may be transformed in vivo . A translocation factor , which was the total 14C in stems, new leaves, and original leaves divided by the 14C in roots, was calculated . The derived TFs were consistently very small, demonstrating the poor translocation of these PPCP/EDCs from roots to upper tissues after uptake. The TF values followed the decreasing order of NPX > DCL > NP > BPA, the opposite observed for plant accumulation. Lettuce displayed lower TFs than collards for the same PPCP/EDCs. For example, the mean TF for BPA was only 0.010 ± 0.003 for lettuce, but was 0.051 ± 0.008 for collards. The much greater accumulation of PPCP/EDCs in roots, as compared to leaves, has been observed in previous studies. For instance, Herklotz et al. found that the levels in leaves were 0.00952 – 0.00503 of those in roots for cabbage grown in nutrient solution spiked with carbamazepine, salbutamol, sulfamethoxazole, and trimethoprim. Doucette et al. reported that the accumulation of NP in leaves was 0.0233 – 0.0167 of that in the roots of crested wheatgrass grown in solution.

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A two compartment model for SA dynamics on the human skin was developed and fitted to data

Some parameters are identifiable to a reasonable degree through model fitting, but there is a large degree of uncertainty in the viral transport efficiencies and the AD kinetic parameters. While this could be a consequence of fitting a limited number of data points with several parameters, the viral load at harvest and risk estimates were well constrained. This large variation in parameters and ‘usefully tight quantitative predictions’ is termed the sloppiness of parameter sensitivities, and has been observed in physics and systems biology. Well-designed experiments may simultaneously reduce uncertainty in the parameters as well as predictions and therefore increasing confidence in predictions. One possible experiment to reduce parameter uncertainty is recording the transpiration and growth rate to fit eq. independently to get at and bt . An interesting outcome of my analysis is the strong association of risk with plant growth conditions. The health risks from consuming lettuce irrigated with recycled wastewater are highest in hydroponic grown lettuce, followed by soil grown lettuce under Sc2 and the least in soil grown lettuce under Sc1 . This difference in risk estimates stems to a large degree from the difference in AD kinetic constants . Increasing katt,s will decrease risk as more viruses will get attached to the growth medium, while increasing kdet,s will have the opposite effect , as more detached viruses are available for uptake by the plant. The combined effect of the AD parameters depends on their magnitudes and is portrayed in Fig. A.4. This result indicates that a better understanding of the virus interaction with the growth environment can lead to an improved understanding of risk. More importantly,livestock fodder system this outcome indicates that soil plays a vital role in the removal of viruses from irrigation water through the adsorption of viral particles. An investigation focused on understanding the influence of soil composition on viral attachment will help refine the transport model.

The risk predicted by this dynamic transport model is higher than the EPA annual infection risk as well as the WHO annual disease burden benchmark. The reasons for this outcome are many-fold. First, there is a significant variability in the reported internalization of viruses in plants. In research of data for modeling NoV transport in plant, I filtered the existing data using the following criteria: 1) human NoV used as the seed agent, 2) presence of quantitative viral results in the growth medium and different locations of the plant. Based on these criteria, the data from represent the best available data on viral internalization and transport in lettuce. However, it is also important to note that a similar study by did not observe human NoV internalization in lettuce. This discrepancy could be due to the specific subspecies of the plant and growth conditions used in the studies. Besides, minor changes such as damages in roots or decrease in humidity of the growing environment can promote pathogen internalization. Alternatively, tracking viral transport through the growth medium and the plant is challenging, which may yield false results due to reaction inhibitions in genome amplification and inferior detection limit. The risk outcome of this study is conservative because it assumes an individual consumes the wastewater irrigated lettuce daily for an entire year. This assumption and the corresponding higher risk estimates are only applicable to a small portion of consumers, while most consumers in the U.S. are likely to have a more diverse diet. While the model outcomes presented here represent the best attempt given the available data, it is also possible that the internalization observed by is an extreme case and and typically internalization occurs to a lesser extent.As previously discussed by others , risk estimates by different NoV dose-response models differed by orders of magnitude. This study primarily aims to introduce a viral transport model without advocating any one dose-response model. The future refinement of pathogen dose-response models will reduce variability in risk estimates.

The risk of consuming lettuce grown in soil as predicted by is higher than my predictions, although I used the results of in both studies. This is a consequence of considering the greater adsorption capability of soil, which is not reflected when assuming a simple input:output ratio. Using different inoculating concentrations of NoV, body weight and consumption rate distributions also contributed to the difference in the outcomes but to a lesser extent. In addition to a transport model predicting the NoV load in lettuce, I explored strategies to reduce the risk of NoV gastroenteritis by increasing holding time of the produce after harvesting or using larger hydroponic culture volumes. Although neither strategy could significantly alleviate the risks, the process highlights two strengths of modeling: 1)It provides analytical support for arguments that would otherwise be less convincing; 2) It predicts outcomes of experiments without the physical resources required to perform them. For instance, the model can be used to explore alternate irrigation schedules to reduce the NoV internalization risk. Modeling also helps encapsulate our understanding of the system and generate hypotheses. For example, simple first-order decay did not produce the trend observed in the water, which suggests that additional mechanisms are at play. I postulated the attachment of virus particles on the walls of the hydroponic system as one possible mechanism and examined the fit of the model. Although viral attachment to glass or other materials has been observed before, here it stands as a hypothesis that can be tested. In addition to generating and testing hypotheses, some of my model assumptions raise broader questions for future research. For example, I assumed that viruses are transported at the transpiration rate from the growth medium to the roots. However, not much is known regarding the role of roots in the internalization of viruses. Investigating the defense mechanisms of plants’ roots to passive viral transport, i.e., through rhizosphere microbiome interactions, may shed light on the broad understanding of plant and microbe interactions. The question of extending this model to other pathogen and plant systems draws attention to the dearth of data in enabling such efforts. While modeling another virus may not require changes to the model, understanding transport in other plants can be challenging.

Data required includes models for growth rate and transpiration, plant growth characteristics including density, water content, as well as internalization studies to determine transport efficiencies. However, from the perspective of risk management, lettuce may be used as the worst-case scenario estimate of risk in water reuse owing to its high consumption with minimal pathogen inactivation by cooking. This worst-case scenario can be used to set water quality standards for irrigation water for the production of fresh produce eaten raw. The models can also be extended to include pathogen transport to the plant tissue from manure/biosolids that are used as organic fertilizer. By assuming that SA transitions from an un-adapted state to an adapted state, the model is grounded in first principles. The stochastic aspect of dose-response emerges naturally from a stochastic simulation of the growth kinetics. In addition, the model predicts carrier outcomes without additional data. Armitage et al. interpret results from several studies to posit that pathogens, including bacteria,hydroponic nft gully show an initial exponential increase in all individuals. We argue that this is not inconsistent with the initial decrease assumption for three reasons. Firstly, the exponential increase is observed in organs like the liver or spleen, and not the whole body or site of inoculation . This does not refute the possibility of an initial decrease at the inoculation site or the whole body. Secondly, the posited decrease is transient, and samples may not have been collected during this window. Thirdly, the magnitude of decrease is low at higher inocula and consequently less detectable. Further, compared to the initial decrease observed when all bacteria are in the S1 state, one would expect 1) no initial decrease if seeding with bacteria all in the S2 state, and 2) a smaller initial decrease if seeding with a mixture of bacteria in the S1 and S2 state. These trends have been observed when pathogens from in-vivo cultures were used for infecting the host . We note that the transition from S1 to S2 is perhaps not instantaneous, and the pathogen population may constitute a continuum of states between S1-S2. When loads were measured in the whole body, a transient decrease was observed in some cases . Clumping of bacteria was offered as a possible explanation, but this does not rule out an actual reduction in viable counts observed in other systems . Armitage et al. also note that non-responders show a subsequent decrease after the initial exponential increase. These were substantiated by measurements from survivors who were killed at later time points. This decrease is probably due to the activation of the adaptive immune response inside the host, which could be incorporated in a within-host variant of the 2C model. Using the concept of IED to evluate reponse, I am able to explain the data with a single IED. It has been observed that the toxic dose of a chemical can vary between individual subjects or with the season.

A similar stochasticity may be expected in IED between individuals which can be attributed to differences in covariates such as body weight, sex, immune history and biological noise. However, assuming this was not necessary to produce an acceptable fit. The model was fit to data by following a two step optimization procedure. Direct multi-objective optimization was not pursued since the objective functions were very different from each other. The deterministic ODE model was easy to evaluate and a global optimization algorithm was employed to guard against local minima while fitting the growth data. Fitting the dose-response data was computationally challenging for 3 reasons: a non-smooth objective function, stochastic simulations have to be repeated many times, and the number of stochastic entities being modeled is not small. Hence, a simple brute-force optimization was adopted. The RH model exhibits a sharp initial decline in SA density and predicts values lower than the observed minimum for each initial load . The 2C model only goes as low as the lowest load observed on the skin. Experiments similar to that of with greater time resolution are necessary to ascertain the time of true minimal SA density. The 2C model stochastic model does not perform as well as the RH model . However, the 2C model fit to dose-response data improves along the Pareto front . It is possible that exploring solutions with a higher growth objective may yield a solution that fits as well as, if not better than, the RH fit to the dose-response data. Moreover, the proposed approach offers advantages over the existing approach in that 1) it is fully mechanistic, and hence is more applicable in other scenarios , and 2) in addition to response outcomes, the proposed approach also accounts for carrier outcomes. Perhaps the most interesting outcome of this study is the incorporation of quorum sensing in dose-response modeling. The rejection of the absence of cooperativity in SA pathogenesis and the adequate fit of cooperativity make a strong case for the cooperativity in action hypothesis. Experimental support for this hypothesis include the well studied Agr system of quorum sensing . In the words of Le. et al, the Agr system “generally enhances pathogenesis by increasing expression of aggressive virulence determinants such as toxins and degradative enzymes”.This system is activated when bacteria reach a certain density, which results in a disease response such as a murine abscess. However, the 2C model posits that quorum sensing enhances bacterial growth rate, for which I propose two possible explanations. The direct explanation is the existence of an as yet undiscovered signaling mechanism responsible for density dependent growth enhancement. A second explanation relates to the events initiating response in a host, which is the interaction of the toxins/enzymes produced by SA with the host tissue. The 2C model captures these dynamics at a higher level of abstraction, with the mathematical variable i representing the amount QS signals and toxins. We can interpret b2 as the rate of enhanced production of these factors.