A scalable model for EPA and fatty acid production by Phaeodactylum tricornutum

Data availability statement: The data underpinning this publication can be accessed from Brunel University London's data repository, Brunelfigshare here under a CCBY licence: https://doi.org/10.17633/rd.brunel.21197263.v1.Copyright © 2022 Gu, Kavanagh and McClure.. Large-scale photoautotrophic production of microalgae has the potential to provide a sustainable supply of omega-3 fatty acids (eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)) for human and animal nutrition. This study presents a kinetic model for the EPA-producing microalga Phaeodactylum tricornutum in photoautotrophic conditions, with light and nitrogen being the growth limiting factors. The model was developed using a dataset obtained from bench-scale (5 L) cultures and was successfully validated against pilot-scale (50 L) cultures. This model is the first to predict the biomass and total fatty acid accumulation along with the EPA concentrations in the biomass and total fatty acid fraction for microalgae. The model was used to develop an optimized repeated-batch strategy; implementation of this led to increases in the biomass and EPA productivities of 50 and 20% respectively. This clearly indicates the potential of the model to be used as a tool in the design, optimization and scale-up of microalgal systems for EPA production.Australian Government Research Training Program Scholarshi

A modelling workflow for quantification of photobioreactor performance

Data availability: Data has been uploaded to the Brunel figshare repository: https://doi.org/10.17633/rd.brunel.23905842Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S1385894723057637?via%3Dihub#s0065 .Copyright © 2023 The Authors. In this work we have developed a comprehensive modelling workflow for the quantification of photobioreactor performance. Computational Fluid Dynamics (CFD) modelling combined with Lagrangian particle tracking was used to characterise the flow field inside the reactor; this information was combined with a Monte-Carlo model of light attenuation and a kinetic growth model to predict the performance of the system over the duration of the entire batch. The CFD model was validated against measurements of the overall hold-up, local hold-up and mixing time for superficial velocities between 0.6 and 6 cm s−1 in a pilot-scale bubble column photobioreactor, with the CFD predictions agreeing with the experimental data. Comparison was also made between the predicted biomass concentration and experimental measurements using the diatom Phaeodactylum tricornutum, with the model predictions being in good agreement with the experimental results. The model was used to investigate a range of operating conditions and reactor designs, with the most promising predicted to give a 40 % increase in the biomass productivity. Results from this work can be used for the in-silico design and optimisation of photobioreactor systems, thereby enabling their wider use as a sustainable production technology

Enabling rational gut microbiome manipulations by understanding gut ecology through experimentally-evidenced in silico models

© 2021 The Author(s). The gut microbiome has emerged as a contributing factor in non-communicable disease, rendering it a target of health-promoting interventions. Yet current understanding of the host-microbiome dynamic is insufficient to predict the variation in intervention outcomes across individuals. We explore the mechanisms that underpin the gut bacterial ecosystem and highlight how a more complete understanding of this ecology will enable improved intervention outcomes. This ecology varies within the gut over space and time. Interventions disrupt these processes, with cascading consequences throughout the ecosystem. In vivo studies cannot isolate and probe these processes at the required spatiotemporal resolutions, and in vitro studies lack the representative complexity required. However, we highlight that, together, both approaches can inform in silico models that integrate cellular-level dynamics, can extrapolate to explain bacterial community outcomes, permit experimentation and observation over ecological processes at high spatiotemporal resolution, and can serve as predictive platforms on which to prototype interventions. Thus, it is a concerted integration of these techniques that will enable rational targeted manipulations of the gut ecosystem.University of Sydney’s Centre for Advanced Food and Engineering; JPMO acknowledges a PhD scholarship from the Faculty of Engineering at the University of Sydney. ERS acknowledges the financial support from the à Beckett Cancer Research Trust (University of Sydney Fellowship)

High throughput genome scale modeling predicts microbial vitamin requirements contribute to gut microbiome community structure

Data availability statement: All data generated or analyzed during this study are included in this published article and its supplementary information files.Copyright © 2022 The Author(s). Human gut microbiome structure and emergent metabolic outputs impact health outcomes. However, what drives such community characteristics remains underexplored. Here, we rely on high throughput genomic reconstruction modeling, to infer the metabolic attributes and nutritional requirements of 816 gut strains, via a framework termed GEMNAST. This has been performed in terms of a group of human vitamins to examine the role vitamin exchanges have at different levels of community organization. We find that only 91 strains can satisfy their vitamin requirements (prototrophs) while the rest show various degrees of auxotrophy/specialization, highlighting their dependence on external sources, such as other members of the microbial community. Further, 79% of the strains in our sample were mapped to 11 distinct vitamin requirement profiles with low phylogenetic consistency. Yet, we find that human gut microbial community enterotype indicators display marked metabolic differences. Prevotella strains display a metabolic profile that can be complemented by strains from other genera often associated with the Prevotella enterotype and agrarian diets, while Bacteroides strains occupy a prototrophic profile. Finally, we identify pre-defined interaction modules (IMs) of gut species from human and mice predicted to be driven by, or highly independent of vitamin exchanges. Our analysis provides mechanistic grounding to gut microbiome stability and to co-abundance-based observations, a fundamental step toward understanding emergent processes that influence health outcomes. Further, our work opens a path to future explorations in the field through applications of GEMNAST to additional nutritional dimensions.University of Sydney (PhD scholarship and à Beckett Cancer Research Trust Fellowship)

Development of dynamic compartment models for industrial aerobic fed-batch fermentation processes

Inhomogeneities in key cultivation variables (e.g., substrate and oxygen concentrations) have been shown to affect key process metrics in large-scale bioreactors. Being able to understand these gradients is hence of key interest from both an industrial and academic perspective. One of the main shortcomings of current modelling approaches is that volume change is not considered. Volume increase is a key feature of fed-batch fermentation processes. Existing models are restricted to simulating snapshots (hundreds of seconds) of industrial processes, which can last several weeks. This study presents a novel methodology that overcomes this limitation by constructing dynamic compartment models for the simulation of fed-batch fermentation processes. This strategy is applied to an industrial aerobic fed-batch fermentation process (40–90 m3) with Saccharomyces cerevisiae. First, it has been validated numerically that the compartmentalization strategy used captures the mixing performance and fluid dynamics. This was done by comparing the mixing times and the local concentration profiles of snapshot fermentation process simulations calculated with both CFD and compartment models. Subsequently, simulations of the entire process have been performed using the dynamic compartment model with kinetics. The simulation allows the spatio-temporal characterization of all process variables (e.g., glucose and DO concentrations), as well as the quantification of the metabolic regimes that the cells experience over time. This strategy enables the rapid characterization and assessment of the impact of gradients on process performance in industrial (aerobic) fed-batch fermentation processes and can be readily generalized to any type of bioreactor and microorganism.Technical University of Denmark; Novozymes A/S

Modelling of industrial-scale bioreactors using the particle lifeline approach

Data Availability: Data have been made available in a repository, details are in the data availability statement.Supplementary material is available online at https://www.sciencedirect.com/science/article/pii/S1369703X23001845?via%3Dihub#sec0030 .Copyright © 2023 The Author(s). A key factor in improving the performance of large-scale bioreactors is understanding the conditions experienced by the cells inside the reactor. This can be challenging due to the practical difficulties involved, hence there is increasing use of simulation to quantify the environmental conditions found in large-scale bioreactors. In this work we have used the particle lifeline approach to quantify the effect of the reactor design on the conditions experienced by two very commonly used industrial organisms (Escherichia coli and Saccharomyces cerevisiae). It was found that the cells in the stirred tank reactor tended to experience longer fluctuations of both starvation and overflow metabolism when compared with those in the bubble column, this behaviour being caused by differences in mixing between the two reactor designs. It was found that a significant (60%) fraction of the population in the stirred tank reactors experienced starvation conditions for a large fraction (>70%) of the time, with exposure to such conditions being likely to affect the cellular metabolism. Results from this work provide a detailed insight into the conditions experienced inside industrial-scale bioreactors operated at realistic conditions. Such data can be leveraged to optimise large-scale reactor designs as well as for the development of scale-down systems.Technical University of Denmark and Novozymes A/S

Inter-examiner reliability of the diagnosis of cervical pillar hyperplasia (CPH) and the correlation between CPH and spinal degenerative joint disease (DJD)

BACKGROUND: Cervical pillar hyperplasia (CPH) is a recently described phenomenon of unknown aetiology. Its clinical importance is poorly understood at the present time; therefore, the objective of this study was to determine (1) the inter-examiner reliability of detecting CPH and (2) if there is a clinically important correlation (r > 0.4) between the number of cervical spine levels showing signs of degenerative joint disease (DJD) and CPH. METHODS: The sample consisted of 320 radiographs of human male and female subjects who ranged from 40 to 79 years of age. The inter-examiner reliability of assessing the presence/absence of pillar hyperplasia was evaluated on 50 neutral lateral radiographs by two examiners using line drawings and it was quantified using the kappa coefficient of concordance. To determine the presence/absence of hyperplastic pillars as well as the presence/absence of DJD at each intervertebral disc and zygapophysial joint, 320 AP open mouth, AP lower cervical and neutral lateral radiographs were then examined. The unpaired t-test at the 5% level of significance was performed to test for a statistically significant difference between the number of levels affected by DJD in patients with and without hyperplasia. The Spearman's rho at the 5% level of significance was performed to quantify the correlation between DJD and age. RESULTS: The inter-examiner reliability of detecting cervical pillar hyperplasia was moderate with a kappa coefficient of 0.51. The unpaired t-test indicated that there was no statistically significant difference (p > 0.05) between the presence/absence of cervical pillar hyperplasia and the number of levels affected by DJD in an age-matched population, regardless of whether all elements were considered together, or the discs and facets were analyzed separately. A Spearman correlation rank of 0.67 (p < 0.05) suggested a moderately strong correlation between the number of elements (i.e. discs/facets) affected, and the age of the individual. CONCLUSION: Cervical pillar hyperplasia is a reasonable concept that requires further research. Its evaluation is easy to learn and acceptably reliable. Previous research has suggested that CPH may affect the cervical lordosis, and therefore, alter biomechanics which may result in premature DJD. This current study, however, indicates that, globally, CPH does not appear to be related to the development of DJD

Segment-specific association between cervical pillar hyperplasia (CPH) and degenerative joint disease (DJD)

BACKGROUND: Cervical pillar hyperplasia (CPH) is a recently described phenomenon of unknown etiology and clinical significance. Global assessment of pillar hyperplasia of the cervical spine as a unit has not shown a relationship with degenerative joint disease, but a more sensible explanation of the architectural influence of CPH on cervical spine biomechanics may be segment-specific. OBJECTIVE: The objective of this study was to determine the level of association between degenerative joint disease (DJD) and cervical pillar hyperplasia (CPH) in an age- and gender-matched sample on a [cervical spine] by-level basis. RESEARCH METHODS: Two-hundred and forty radiographs were collected from subjects ranging in age between 40 and 69 years. The two primary outcome measures used in the study were the segmental presence/absence of cervical pillar hyperplasia from C3 to C6, and segment-specific presence/absence of degenerative joint disease from C1 to C7. Contingency Coefficients, at the 5% level of significance, at each level, were used to determine the strength of the association between CPH and DJD. Odds Ratios (OR) with their 95% Confidence Intervals (95% CI) were also calculated at each level to assess the strength of the association. RESULTS: Our study suggests that an approximately two-to-one odds, or a weak-to-moderate correlation, exists at C4 and C5 CPH and adjacent level degenerative disc disease (DDD); with the strongest (overall) associations demonstrated between C4 CPH and C4–5 DDD and between C5 CPH and C5–6 DDD. Age-stratified results demonstrated a similar pattern of association, even reaching the initially hypothesized OR ≥ 5.0 (95% CI > 1.0) or "moderately-strong correlation of C ≥ .4 (p ≤ .05)" in some age categories, including the 40–44, 50–59, and 60–64 years of age subgroups; these ORs were as follows: OR = 5.5 (95% CI 1.39–21.59); OR = 6.7 (95% CI 1.65–27.34); and OR = 5.3 (95% CI 1.35–21.14), respectively. CONCLUSION: Our results suggest that CPH has around two-to-one odds, that is, only a weak-to-moderate association with the presence of DJD (DDD component) at specific cervical spine levels; therefore, CPH may be but one of several factors that contributes (to a clinically important degree) to the development of DJD at specific levels in the cervical spine

Effects of Payena dasyphylla (Miq.) on hyaluronidase enzyme activity and metalloproteinases protein expressions in interleukin-1beta stimulated human chondrocytes cells

Background: Hyaluronidases have been found as the target enzymes in the development of osteoarthritis (OA) disease. While there is still no curative treatment for this disease, recent studies on the treatment of OA were focused on the effectiveness of natural products which are expected to improve the symptoms with minimal side effects. The aim of this study was to screen selected Malaysian plants on their anti-hyaluronidase activity as well as to evaluate the active plant and its derived fractions on its potential anti-arthritic and antioxidant activities.Methods: A total of 20 methanolic crude extracts (bark and leaf) from ten different plants were screened using a colorimetric hyaluronidase enzymatic assay. The active plant extract (Payena dasyphylla) was then studied for its hyaluronidase inhibitory activity in the interleukin-1β (IL-1β) stimulated human chondrocytes cell line (NHAC-kn) using zymography method. The Payena dasyphylla methanolic bark extract was then fractionated into several fractions in where the ethyl acetate (EA) fraction was evaluated for its inhibitory effects on the HYAL1 and HYAL2 gene expressions using reverse transcription-polymerase chain reaction (RT-PCR) technique. While the MMP-3 and MMP-13 protein expressions were evaluated using western blot method. The phenolic and flavonoid contents of the three fractions as well as the antioxidant property of the EA fraction were also evaluated.Results: Bark extract of Payena dasyphylla (100 μg/ml) showed the highest inhibitory activity against bovine testicular hyaluronidase with 91.63%. The plant extract also inhibited hyaluronidase expression in the cultured human chondrocyte cells in response to IL-1β (100 ng/ml). Similarly, treatment with Payena dasyphylla ethyl acetate (EA) fraction (100 μg/ml) inhibited the HYAL1 and HYAL2 mRNA gene expressions as well as MMP-3 and MMP-13 protein expression in a dose dependent manner. Payena dasyphylla EA fraction has demonstrated the highest amount of phenolic and flavonoid content with 168.62 ± 10.93 mg GAE/g and 95.96 ± 2.96 mg RE/g respectively as compared to water and hexane fractions. In addition, the Payena dasyphylla EA fraction showed strong antioxidant activity with IC50 value of 11.64 ± 1.69 μg/mL.Conclusion: These findings have shown that Payena dasyphylla might contained potential phenolic compounds that inhibiting the key enzyme in osteoarthritis development, which is the hyaluronidase enzyme through interruption of HYAL1 and HYAL1 gene expressions. The degradation of cartilage could also be inhibited by the plant through suppression of MMP-3 and MMP-13 protein expressions. We also reported that the inhibitory effect of Payena dasyphylla on hyaluronidase activity and expression might be due to its anti-oxidant property