The labor category does not appear clearly on the chart because of the low need for labor hours since the indoor facility is highly automated.In both DSP scenarios, facility-dependent costs have the highest cost impact. Insurance, local taxes, and other overhead expenses are estimated to be 1%, 2%, and 5% of the section’s DFC, respectively. Maintenance costs are also included in this category and estimated to be 10% of equipment purchase prices. Facility dependent cost estimation parameters are shown in Tables S9 and S10. Consumables account for 38% of the DSP facility with chromatography due to the high cost of Capto S resin that is changed every 100 cycles. The effect of varying resin binding capacity to the product on the DSP AOC and COGS is shown in Figure 3d.Transgenic production models were resized based on scenario design requirement for production levels ranging from 10–150 MT and expression levels ranging from 0.5–2.5 g/kg, while keeping the scheduling parameters the same from base case models. The significant impact of expression level on CAPEX and COGS is elucidated in Figure 4a–c. Production level shows a very small decline in COGS for indoor upstream facility and a linear increase in CAPEX with increasing production level.
On the other hand, the field upstream facility showed a significant increase in COGS at lower production levels due to the minimum ownership costs of field equipment regardless of the small acreage size. DSP followed the expected behavior that economy of scale dictates, weed dryer with sharp decrease in COGS at lower production levels and diminishing returns at higher production levels. The deviation from linear trend at 150 MT/year in field upstream and DSP is likely due to the model’s specified equipment maximum rating, which allows for the inclusion of a new equipment in parallel beyond this rating.The impact of varying the highest cost drivers in each of the facility’s category by 25% on COGS is portrayed as a tornado diagram in Figure 5c. Field labor was the most sensitive cost variable, having the highest impact on the COGS, followed by the ultrafiltration membrane, which is replaced every 30 cycles. In this model, we assume a relatively high downstream recovery of the protein from harvest to formulation. The reason for this assumption is that spinach, being edible crop, allows for a lower target product purity and a consequently fewer DSP steps. It is particularly important to focus resources on maximizing downstream recovery during process development because it ultimately affects plant biomass and spray volume requirement upstream to appropriately compensate for these losses, which in turn affects equipment sizing in DSP based on the amount of plant material to be processed.
The unit operations were resized according to the scenario design requirement for downstream recovery ranging from 50 to 95% while scheduling parameters were left unchanged. This effect of downstream recovery on theAlthough our analysis indicates a relatively high COGS range for a sugar substitute, there are unrealized costs savings from thaumatin use due to its unique sweetness intensity. Thaumatin’s use in extremely small quantities is essentially why it is considered a noncaloric sweetener, as it provides only 4 calories per gram. Sensory evaluation studies have found that a sample with 5% sucrose +4.6 ppm thaumatin II had similar sweetness as a 10% sucrose control with minimal lingering aftertaste, suggesting that up to one-half of the sugar could be replaced by thaumatin II . SSBs including sodas, fruit drinks, and sport drinks account for 50% of the total added sugar in Western diets, and therefore provide an attractive avenue for thaumatin emergence as a sugar substitute. The incorporation of thaumatin by the industry not only offers a tool to help decelerate the obesity epidemic caused by increased childhood sugar intake decades ago, but also provides itself with a more economically viable solution. Firstly, as sugar taxations emerge, sugar reduction becomes a financial incentive. Secondly, the reduction of sugar and the addition of thaumatin to retain the same level of sweetness has the potential to save millions of dollars per day on the cost of sweetening beverages.
Assuming that the average “standard” sucrose concentration in SSBs is 35.5 g per 12 fl oz. drink ~10% , and a $0.30/kg sugar price, Figure 6 shows the potential savings from using thaumatin to reduce sugar content by 20%, 30%, and 50%, while maintaining the same sweetness as the standard for a range of thaumatin purchase prices. The amount of thaumatin needed to obtain the same sweetness as a 10% solution in each sugar reduction scenario was calculated using the sensory regression analysis included in a published GRAS notice . Table 3 shows the daily and annual amount of thaumatin needed for each sugar reductions scenario, assuming that one billion 12 fl oz drinks are to be sweetened per day. Successful implementation of thaumatin in this avenue can liberate R&D resources to improve expression levels and increase production volumes, both of which have a substantial impact on COGS reduction, as we have demonstrated.Our preliminary engineering facility design indicates the feasibility of thaumatin manufacturing by various molecular farming platforms. The most economic method is the field grown ethanol-inducible, transgenic N. tabacum, assuming a downstream facility without chromatography . It remains unclear whether heat incubation is sufficient to achieve the desired purity for a safe product without the inclusion of chromatography on a large-scale. In a previous plant-made food safety product techno-economic analysis, a chromatography unit was included for protein purification from N. benthamiana; however, heat precipitation of host cell proteins was not included as a purification step. We also demonstrate the importance of resin selection and thorough chromatography operation optimization by evaluating the cost benefit of maximizing resin binding capacity to target product. Of course, further work is needed to verify whether the use of column chromatography is needed. Transient production of thaumatin in the edible crop Spinacia oleracea was also economically competitive and captures the benefits of obviating the need for an intensive DSP. According to this analysis, the cost to produce a kg of fresh weight of spinach is $0.10, as opposed to a cheaper price for tobacco . This is attributed to the higher cost of the seeds of spinach, the longer turnaround time assumed for spinach, and the higher plant density assumed for tobacco. It is evident that field operation is very labor intensive, due to the low recipe cycle time of 2 days, which is different than the traditional time frame of growing those crops. The potential for high intra-batch variations in product yield and quality due to meteorological factors is one of the concerns of using field grown plant material for this application. These variations in turns cause inconsistency in key facility performance parameters that should be quantified using a probabilistic approach and communicated to stakeholders and will be addressed in a follow-up communication. The cost of obtaining a more controlled supply of product is reflected in the indoor upstream facilities CAPEX and COGS. This should facilitate decision making when assessing the risk and reward of each scenario. The large-scale recombinant production of thaumatin can address the growing market need for natural, safe, non-caloric sweeteners. Like stevia, the advent of thaumatin as a sugar substitute is contingent on the feasibility of its large-scale manufacturing which was addressed in this work. However, there are also social, cultural, cannabis curing and behavioral factors impacting sugar consumption habits that were not considered. Consumer’s preference of such products will open the door for more plant-made biologics for food and beverage applications, which could drive the adoption of cost-effective solutions to rising challenges through environmentally friendly and sustainable processes.As the demand for agricultural production grows and additional challenges arise as our climate changes, there is increasing interest in harnessing beneficial plant-microbe interactions to improve promote plant growth and health. Furthermore, though plants and microbes have been co-evolving for millions of years, human agriculture has only been in practice for 12,000 years. Plant breeding and agricultural processes such as chemical usage, monoculture, and annual tillage are far removed from how plants naturally grow and thrive, and as such, there is a need to understand how agricultural and breeding practices impact plant-microbe interactions. There remain key open questions regarding the effects of plant breeding for agriculturally beneficial traits, transmission of plant microbiota, and overall importance of microbial community living on the above ground surfaces of plants, a habitat known as the phyllosphere.The plant host study system in this work is the modern tomato plant, Solanum lycopersicum. Tomatoes have an extensive and interesting history of domestication.
Their wild ancestors, Solanum pimpinellifolium, originate from the Andean region of South America. They are thought to have been domesticated initially in Mexico and then brought to Europe in the 1500s. Though wild tomatoes have a large genetic diversity, domesticated cultivars are estimated to contain less than 5% of this genetic diversity due to a history of inbreeding and back crossing of domesticated lines. It was not until the early 1900s that breeders began to cross S. lycopersicum with wild lines to reintroduce genetic diversity and select for desirable traits such as disease resistance. The tomato plant is an ideal host system for various reasons. First, researchers and breeders have access to thousands of tomato accessions through the UC Davis Tomato Genetics Resource Center , allowing for consistent and reliable control over host genetics. Furthermore, tomato plants can be easily propagated in controlled-temperature growth chambers, the greenhouse, or the field. Finally, there is an applied interest in work such as this, as the tomato industry in the US produces 2.6 billion dollars worth of fresh and market tomatoes , and locally, is one of California’s top ten most valued agricultural products .Many of the ways in which microbial communities interact with their host is through the host immune system. As such, a cursory understanding of the plant immune system, and how this compares to immunity in other systems, is necessary to fully understand how microbes influence host health. The adaptive immune system is thought to have arisen in jawed fish ≈500 million years ago, whereas the innate immune system likely dates back to early eukaryotic cells themselves. As microbial communities greatly pre-date the existence of multicellular eukaryotes, both branches of the immune system evolved in the presence of microbes, and it follows that tolerance for commensal microbiota must have been a key factor in shaping the evolution of immunity. Innate immunity, found across all kingdoms of life, is non-specific and responds broadly to ‘non-self’ invaders. Its hallmarks include protective physical barriers and general pattern recognition receptors that sense non-self signals and elicit host responses. Adaptive immunity is unique to vertebrates and responds to specific pathogens through detection of antigens via somatically-generated receptors and specialized white blood cells , resulting in immunological memory, in which the organism is protected from future infection . Broadly speaking, the adaptive immune response is highly specific to particular pathogens and can change over the course of a host’s lifetime whereas the innate immune response is a general resistance that can only respond to selection across host generations. Plant innate immunity consists of two primary responses to microbes. The first branch of the immune system recognizes microbial- or pathogen-associated molecular patterns through the use of transmembrane pattern recognition receptors and results in pattern-triggered immunity. However, many plant pathogens have evolved to overcome these defenses through the use of effectors. Plants with resistance genes for specific pathogens can detect the effectors through NB-LRR proteins, which represent the second response to microbes: effector triggered immunity. Additionally, plants have physical barriers to infection such as cell wall defenses, and they can also secrete antimicrobial peptides to ward off infection. Although vertebrate adaptive immunity is typically considered more specific, plant immunity is also the result of specific recognition, either of pathogen effectors or molecular patterns, and immune ‘priming’ in plants has been shown repeatedly. As is becoming increasingly evident, in addition to its well-studied role in preventing pathogen establishment, the immune system also influences both the composition and abundance of non-pathogenic microbiota. In mammals, this is best studied in the gut microbiome, where differentiating between these diverse commensals and colonizing pathogens is clearly a highly complex problem.