Optimizing a High Performing Multiplex-CRISPRi P. putida strain with Integrated Metabolomics and 13C-Metabolic Flux Analyses

Microbial cell factory development often faces bottlenecks after initial rounds of design-build-test-learn (DBTL) cycles as engineered producers respond unpredictably to further genetic modifications. Thus, deciphering metabolic flux and correcting bottlenecks are key components of DBTL cycles. Here, a 14-gene edited Pseudomonas putida KT2440 strain for heterologous indigoidine production was examined using both 13C-metabolic flux analysis (13C-MFA) and metabolite measurements. The results indicated the conservation of the cyclic Entner-Doudoroff (ED)-EMP pathway flux, downregulation of the TCA cycle and pyruvate shunt, and glyoxylate shunt activation. At the metabolite level, the CRISPR/dCpf1-interference mediated multiplex repression decreased gluconate/2-ketogluconate secretion and altered several intracellular TCA metabolite concentrations, leading to succinate overflow. Further strain engineering based on the metabolic knowledge first employed an optimal ribosome binding site (RBS) to achieve stronger product-substrate growth coupling (1.6-fold increase). Then, deletion strains were constructed using ssDNA recombineering. Of the five strains tested, deletion of the PHA operon (ΔphaAZC-IID) resulted in a 2.2-fold increase in growth phase production compared to the optimal RBS construct. After 72 h of batch cultivation, the ΔphaAZC-IID strain had 1.5-fold and 1.8-fold increases of indigoidine titer compared to the improved RBS construct and the original strain, respectively. Overall, the findings provided actionable DBTL targets as well as insights into physiological responses and flux buffering when new recombineering tools were used for engineering P. putida KT2440.

Response of sweet cherry buds and twigs to temperature changes – evaluated by the determination of the degradation and synthesis of sucrose

This study was undertaken to determine the degradation and synthesis of sucrose (Suc) in sweet cherry buds and the twig tissue response to a sequence of environmental temperature changes (cold (orchard) – warm (controlled temperature of ∼22 °C) – cold (orchard)). The results of two years’ (2016, 2017) findings were compared with the buds of trees and the buds of twigs in November/December in northeast Germany. The Suc content in the buds of trees and the buds of twigs under natural conditions was stable. Temperatures of ∼22 °C resulted in a significant (Suc) degradation (62%, from 39 to 15 mg/g DW) in the buds of twigs after 21 days (day of the year (DOY) 340). The significant re-synthesis (66%, to 25 mg/g DW after 21 days, DOY 361) in the orchard is noteworthy, and highlights the Suc value as a cryoprotective saccharide. The marked changes in the Suc, glucose, and fructose contents of the twigs exposed to a cold-warm-cold sequence (< DOY 319, DOY 319–340, DOY 340–361), lead to the conclusion that this adaptation is the result of tissue- and cold-specific sucrose invertases/synthases. The effect of low-temperature-active enzymes explains the role of Suc in the buds of trees during the winter rest. When using twigs for plant physiological examinations during the winter rest, results on a metabolite level should be considered when drawing conclusions concerning the overall tree physiology.

Metabolite Alternations in the Dopamine Circuit Associated with Methamphetamine-Related Psychotic Symptoms: A Proton Magnetic Resonance Spectroscopy Study

Objective: Chronic METH use results in neurodegenerative alternations in the human brain. The present study aimed to assess the long-term METH impact on brain metabolite concentrations in cases meeting the DSM-5 criteria regarding METH use. Method: We recruited 42 METH users meeting the DSM-5 criteria and 21 healthy controls. Psychotic signs were measured using the Positive and Negative Syndrome Scale (PANSS). Proton magnetic resonance spectroscopy (1HMRS) evaluating Myo-inositol (Ml), Choline (Cho), Glutamine plus Glutamate (Glx), N-acetyl aspartate (NAA), and Creatine (Cre) were obtained in the dopaminergic pathway (Frontal Cortex, Substantia nigra, Ventral Tegmental Area (VTA), Nucleus Accumbens (NAc), Hippocampus, Striatum,) the subjects. All participants collected urine specimens for 24 hours to measure presence of specific metabolites including METH metabolite level, 5-Hydroxy indoleacetic acid metabolite (for serotonin level monitoring), and metanephrine metabolite (for dopamine level monitoring). Results: Dopamine and Serotonin increased in the METH group (P < 0.001). METH caused an increase in the Cre (P < 0.001) and a decline in the Glx (P < 0.001), NAA (P = 0.008), and MI (P < 0.001) metabolite concentrations of dopamine circuits in METH users in comparison with healthy subjects. We found no change in Cho metabolite concentration. Psychological data and the neurometabolite concentrations in the studied area of the brain were significantly correlated. Conclusion: There is an association between METH use and active neurodegeneration in the dopamine circuit, and it causes serious mental illness. 1HMRS can detect patient’s deterioration and progression of disease as well as follow-up management in patients with METH use disorder.

117 Nutrition Modelling: What Can the Pet Field Learn (or Steal) from Recent Directions in Other Species?

Nutrition modelling has been the cornerstone of feed formulation and diet optimization in animal production systems for decades. Since the 1970s and 1980s, mechanistic models of nutrient digestion, absorption, metabolism, growth and milk/egg production have been developed and implemented to (1) amass our cumulative biological knowledge and develop theories of regulation, (2) identify knowledge gaps, and (3) propose means to manipulate nutrient dynamics in the animal. At the nutrient and metabolite level, many commonalities exist and parallels found between species. In fact, several second generation models originate from other species or research fields, and many current/existing models may be advanced by examination and consideration of models developed in other species. Many such mathematical models are implemented in practice as ‘decision support systems’ or ‘opportunity analysis tools’, in order to examine a variety of (feeding or management) scenarios for their potential outcomes, with the goal of providing targeted nutrition, improving performance, reducing cost and minimizing environmental impact. More recently, partnering artificial intelligence/machine learning modelling methodologies with newly available big data streams has ushered in a new era of possibilities for data extraction and modelling in animal systems. The niche for this type of modelling in animal production appears to be (1) pattern recognition (e.g. disease detection, activity) and (2) strong predictive/forecasting abilities (e.g. bodyweight, milk, egg production). There also appears strong potential for these two seemingly divergent modelling approaches to be integrated – for example, in precision feeding systems, or in utilizing the abundance of sensor data to better drive or develop causal-pathway based mechanistic models. This talk will broadly review trends and advances in agriculture animal species modelling, and suggest what may be borrowed, stolen or serve as inspiration to advance nutrition models in companion species.

Modulation of Dorsolateral Prefrontal Cortex Glutamate/Glutamine Levels Following Repetitive Transcranial Magnetic Stimulation in Young Adults With Autism

Altered excitatory and inhibitory neurotransmission has been implicated in autism spectrum disorder (ASD). Interventions using repetitive transcranial magnetic stimulation (rTMS) to enhance or inhibit cortical excitability are under study for various targets, though the mechanistic effects of rTMS have yet to be examined in ASD. Here, we examined whether an excitatory rTMS treatment course modulates glutamatergic (Glx) or γ-aminobutyric acid (GABA) metabolite levels in emerging adults with ASD. Twenty-eight participants with ASD and executive function impairment [23.3 ± 4.69 years; seven-female] underwent two magnetic resonance spectroscopy (MRS) scans of the left dorsolateral prefrontal cortex (DLPFC). MRS scans were acquired before and after participants with ASD were randomized to receive a 20-session course of active or sham rTMS to the DLPFC. Baseline MRS data was available for 19 typically developing controls [23.8 ± 4.47 years; six-female]. Metabolite levels for Glx and GABA+ were compared between ASD and control groups, at baseline, and metabolite level change, pre-to-post-rTMS treatment, was compared in ASD participants that underwent active vs. sham rTMS. Absolute change in Glx was greater in the active vs. sham-rTMS group [F(1,19) = 6.54, p = 0.02], though the absolute change in GABA+ did not differ between groups. We also examined how baseline metabolite levels related to pre/post-rTMS metabolite level change, in the active vs. sham groups. rTMS group moderated the relation between baseline Glx and pre-to-post-rTMS Glx change, such that baseline Glx predicted Glx change in the active-rTMS group only [b = 1.52, SE = 0.32, t(18) = 4.74, p &lt; 0.001]; Glx levels increased when baseline levels were lower, and decreased when baseline levels were higher. Our results indicate that an interventional course of excitatory rTMS to the DLPFC may modulate local Glx levels in emerging adults with ASD, and align with prior reports of glutamatergic alterations following rTMS. Interventional studies that track glutamatergic markers may provide mechanistic insights into the therapeutic potential of rTMS in ASD.Clinical Trial Registration:Clinicaltrials.gov (ID: NCT02311751), https://clinicaltrials.gov/ct2/show/NCT02311751?term=ameis&amp;rank=1; NCT02311751.

GC-MS-based metabolite profiling of key differential metabolites between superior and inferior spikelets of rice during the grain filling stage

Background The asynchronous filling between superior spikelets (SS) and inferior spikelets (IS) in rice has become a research hotspot. The stagnant development and poor grain filling of IS limit yields and the formation of good quality rice. A large number of studies on this phenomenon have been carried out from the genome, transcriptome and proteome level, indicating that asynchronous filling of SS and IS filling is a complex, but orderly physiological and biochemical process involving changes of a large number of genes, protein expression and modification. However, the analysis of metabolomics differences between SS and IS is rarely reported currently. Results This study utilized untargeted metabolomics and identified 162 metabolites in rice spikelets. Among them, 17 differential metabolites associated with unsynchronized grain filling between SS and IS, 27 metabolites were related to the stagnant development of IS and 35 metabolites related to the lower maximum grain-filling rate of IS compared with the SS. We found that soluble sugars were an important metabolite during grain filling for SS and IS. Absolute quantification was used to further analyze the dynamic changes of 4 types of soluble sugars (sucrose, fructose, glucose, and trehalose) between SS and IS. The results showed that sucrose and trehalose were closely associated with the dynamic characteristics of grain filling between SS and IS. The application of exogenous sugar showed that trehalose functioned as a key sugar signal during grain filling of IS. Trehalose regulated the expression of genes related to sucrose conversion and starch synthesis, thereby promoting the conversion of sucrose to starch. The difference in the spatiotemporal expression of TPS-2 and TPP-1 between SS and IS was an important reason that led to the asynchronous change in the trehalose content between SS and IS. Conclusions The results from this study are helpful for understanding the difference in grain filling between SS and IS at the metabolite level. In addition, the present results can also provide a theoretical basis for the next step of using metabolites to regulate the filling of IS.

GC-MS-Based Metabolite Profiling of Key Differential Metabolites Between Superior and Inferior Spikelets of Rice During the Grain Filling Stage

Background:The asynchronous filling between superior spikelets (SS) and inferior spikelets (IS) in rice has become a research hotspot. The stagnant development and poor grain filling of IS limit yields and the formation of good quality rice. A large number of studies on this phenomenon have been carried out from the genome, transcriptome and proteome level, indicating that asynchronous filling of SS and IS filling is a complex, but orderly physiological and biochemical process involving changes of a large number of genes, protein expression and modification. However, the analysis of metabolomics differences between SS and IS is rarely reported currently.Results:This study utilized untargeted metabolomics and identified 162 metabolites in rice spikelets. Among them, 17 differential metabolites associated with unsynchronized grain filling between superior spikelets (SS) and IS, 27 metabolites were related to the stagnant development of IS and 35 metabolites related to the lower maximum grain-filling rate of IS compared with the SS. We found that soluble sugars were an important metabolite during grain filling for SS and IS. Absolute quantification was used to further analyze the dynamic changes of 4 types of soluble sugars (sucrose, fructose, glucose, and trehalose) between SS and IS. The results showed that sucrose and trehalose were closely associated with the dynamic characteristics of grain filling between SS and IS. The application of exogenous sugar showed that trehalose functioned as a key sugar signal during grain filling. Trehalose regulated the expression of genes related to sucrose conversion and starch synthesis, thereby promoting the conversion of sucrose to starch. The difference in the spatiotemporal expression of TPS-2 and TPP-1 between SS and IS was an important reason that led to the difference in trehalose contents between SS and IS.Conclusions:The results from this study are helpful for understanding the difference in grain filling between SS and IS at the metabolite level. In addition, the present results can also provide a theoretical basis for the next step of using metabolites to regulate the filling of IS.

Modulation of Phosphate Deficiency-Induced Metabolic Changes by Iron Availability in Arabidopsis thaliana

Concurrent suboptimal supply of several nutrients requires the coordination of nutrient-specific transcriptional, phenotypic, and metabolic changes in plants in order to optimize growth and development in most agricultural and natural ecosystems. Phosphate (Pi) and iron (Fe) deficiency induce overlapping but mostly opposing transcriptional and root growth responses in Arabidopsis thaliana. On the metabolite level, Pi deficiency negatively modulates Fe deficiency-induced coumarin accumulation, which is controlled by Fe as well as Pi deficiency response regulators. Here, we report the impact of Fe availability on seedling growth under Pi limiting conditions and on Pi deficiency-induced accumulation of amino acids and organic acids, which play important roles in Pi use efficiency. Fe deficiency in Pi replete conditions hardly changed growth and metabolite profiles in roots and shoots of Arabidopsis thaliana, but partially rescued growth under conditions of Pi starvation and severely modulated Pi deficiency-induced metabolic adjustments. Analysis of T-DNA insertion lines revealed the concerted coordination of metabolic profiles by regulators of Fe (FIT, bHLH104, BRUTUS, PYE) as well as of Pi (SPX1, PHR1, PHL1, bHLH32) starvation responses. The results show the interdependency of Pi and Fe availability and the interplay between Pi and Fe starvation signaling on the generation of plant metabolite profiles.

CYP2D6 Genotyping for Personalized Therapy of Tamoxifen in Indonesian Women with ER+ Breast Cancer

Tamoxifen is a Selective Estrogen-Receptor Modulator (SERM) commonly prescribed for standard of care in estrogen receptor positive (ER+) breast cancer as an adjuvant therapy. Tamoxifen is metabolized by CYP2D6 into its active metabolite, endoxifen, which has been known to play an important role in reducing risk of ER+ breast cancer recurrence. CYP2D6 is a highly polymorphic gene with more than 100 alleles. The phenotype of this gene is categorized into ultrarapid metabolizer (UM), normal metabolizer (NM), intermediate metabolizer (IM), and poor metabolizer (PM). Certain CYP2D6 polymorphisms may cause reduced activity of this enzyme. Studies have found that reduced CYP2D6 activity in IM and PM patients causes low efficacy of standard tamoxifen therapy. This study aims to observe the distribution of CYP2D6 alleles and its correlation with endoxifen levels in Indonesian ER+ breast cancer patients. 151 patients who have received tamoxifen therapy for at least eight weeks were recruited prospectively. DNA and blood samples were collected with buccal swab and finger-prick methods, respectively. Genotyping was performed using the qPCR method while metabolite level measurement was performed using high performance liquid chromatography tandem mass spectrometry. We found that 40.67% of ER+ breast cancer patients recruited were IM. CYP2D6*10 was the most abundant allele (0.288) in this population, and *10/*36 was the most frequently observed diplotype (0.236). Endoxifen levels between the NM-PM, NM-IM, and IM-PM were statistically significant (p-value = 6.26 x 10-5, 9.12 x 10-5, and 4.714 x 10-3, respectively), and dose increase of tamoxifen to 40 mg daily successfully increased endoxifen levels in IMs to a similar level with NMs at baseline. Given these findings, implementing pharmacogenomic testing of CYP2D6 on ER+ breast cancer women who are about to undergo tamoxifen therapy may be beneficial to increase the likelihood of achieving expected endoxifen levels, thus better treatment efficacy.

Characterization of the 1H-MRS Metabolite Spectra in Transgender Men with Gender Dysphoria and Cisgender People

Much research has been conducted on sexual differences of the human brain to determine whether and to what extent a brain gender exists. Consequently, a variety of studies using different neuroimaging techniques attempted to identify the existence of a brain phenotype in people with gender dysphoria (GD). However, to date, brain sexual differences at the metabolite level using magnetic resonance spectroscopy (1H-MRS) have not been explored in transgender people. In this study, 28 cisgender men (CM) and 34 cisgender women (CW) and 29 transgender men with GD (TMGD) underwent 1H-MRS at 3 Tesla MRI to characterize common brain metabolites. Specifically, levels of N–acetyl aspartate (NAA), choline (Cho), creatine (Cr), glutamate and glutamine (Glx), and myo-inositol + glycine (mI + Gly) were assessed in two brain regions, the amygdala-anterior hippocampus and the lateral parietal cortex. The results indicated a sex-assigned at birth pattern for Cho/Cr in the amygdala of TMGD. In the parietal cortex, a sex-assigned at birth and an intermediate pattern were found. Though assessed post-hoc, exploration of the age of onset of GD in TMGD demonstrated within-group differences in absolute NAA and relative Cho/Cr levels, suggestive for a possible developmental trend. While brain metabolite levels in TMGD resembled those of CW, some interesting findings, such as modulation of metabolite concentrations by age of onset of GD, warrant future inquiry.