Difference between revisions of "Part:BBa K857000"

Latest revision as of 05:10, 21 October 2021

acetaldehyde dehydrogenase

Coding protein for acetaldehyde dehydrogenase convert acetaldehyde into acetyl-CoA.

CH3CHO + NAD+ + CoA → acetyl-CoA + NADH + H+

This part was designed by the 2012 iGEM UC Merced team and it is a gene that is involved in the E. Coli glucose metabolism pathway. Our team characterized this part by performing an in silico knockout of this gene. Using quantitative analysis, we discovered that its deletion does not affect the growth of E. Coli when under optimal conditions to produce a 4:1 hydrogen production to glucose uptake ratio. More importantly, we identified possible non-lethal gene deletions that may help maximize hydrogen production in the dark fermentation process.

First, we measured the growth of E. Coli bacteria under the conditions in which the insertion of mhpF allows the production of hydrogen to glucose uptake ratio to be 4:1. This was done using the Constraint Model Based Reconstruction and Analysis (COBRA) toolbox on Matlab platform which allowed us to constrain the uptake of glucose and hydrogen release to a ratio of 4:1 on our E. Coli glucose metabolism model. Our results were performed using Flux Balance Analysis (FBA) on the Core E. Coli Model by the Systems Biology Research Group at the University of California generated from the current gene expression data on E. coli.

Figure 1. Demonstrates the growth of E.coli when subject to the hydrogen release to glucose uptake requirement.

Our results showed that when the MhpF gene is introduced, E. Coli growth is higher under anaerobic conditions than aerobic conditions when under stress requirement to produce a 4:1 hydrogen to glucose ratio. This was achieved by setting oxygen flux values to both unlimited and zero for aerobic and anaerobic conditions respectively, whilst measuring E. coli’s growth in rate per hour. Growth measurements were done as a quantitative measure of how E.coli performs against the gene modification added to its metabolism.

Furthermore, our analysis from Flux Balance Analysis (FBA) validated team UC Merced hypothesis that removing IdhA, pfIB and adhE from E. coli fermentation pathway and replacing it with mhpF, pyruvate decarboxylase and ferredoxin oxidoreductase. This was achieved by performing in silico knockouts of IdhA, pfIB and adhE on the E. coli model and multiple gene insertions of mhpF, pyruvate decarboxylate and ferredoxin and looking at how the shift in metabolism network improve hydrogen yield under anaerobic condition.

Figure 2.Shift in metabolism flux network when E. coli model is subjected to hydrogen release to glucose uptake 4:1 ratio under aerobic conditions (left) and anaerobic conditions(right).

Next, we analyzed the effect of deleting the mhpF gene on the growth rate of E. Coli (in biomass/hour). The quantitative analysis shows that the growth remained the same, which indicates that the mhpF gene does not affect the growth rate of E. Coli. This served as motivation to perform more single gene deletions on the E.coli model. We analyzed the effect of creating knockouts of all the genes involved in glucose metabolism on the bacteria by examining the lethality of deleting each gene. Team UC Merced attempted to create knockouts of three genes, and below we present suggestions regarding the genes in the dark fermentation process that can be deleted without being lethal. Deletions of genes in the dark fermentation process, a form of anaerobic conversion would facilitate the conversion of organic substrate to biohydrogen. (see Table 1) For instance our analysis from the gene deletion suggested that the deletion zwf gene( glucose-6-phosphate 1-dehydrogenase) which is principal in the pentose pathway would be lethal to the E. coli. It turns out that zwf and mphF gene is overexpressed in the dark fermentation process. Even though both are very necessary for hydrogen production, mphF deletion would not result in much difference in the flux. Further our metabolic network flux predicts that the overexpression of zwf leads to the diversion of carbon flux through the PP pathway and hence result in an increase in the efficiency of the production of H2. Finally, a robustness analysis was performed to verify the validity of the results by setting fixed amounts of glucose and hydrogen and measuring the growth as a function of the oxygen concentration. This analysis was performed to demonstrate the strength of our model's prediction. The linear graph predicts a linear rise in growth with an intermittent increase in glucose intake. This agrees and supports our previous data which suggested that mphF is implied in the increase in growth of E.coli when subject to the condition stipulated above.



In sum , using metabolic modeling allow for in silico gene knockouts and metabolic analysis that unveiled non lethal gene deletions and insertion that would prove useful for the generation of biohydrogen from E.coli. Using metabolic modeling, it is easier to generate genetic changes that would optimize hydrogen production from E.coli. graph robustness

Finally, a robustness analysis was performed to verify the validity of the results by setting fixed amounts of glucose and hydrogen and measuring the growth as a function of the oxygen concentration. Table 1: Possible gene deletions and their measure effects on E. coli.

Contribution: XHD-Wuhan-Pro-China 2021

Characterization of Sortase BBa_K3925009 (and comparison to BBa_K857000)

pSB-BBa_K857000 only contains the alcohol dehydrogenase of BBa_K857000. In order to improve its enzyme activity, we modified BBa_K3925009. In addition to the alcohol dehydrogenase of BBa_K857000, pSB-BBa_K3925009 also has BBa_K3925005-NAD synthetase gene (nadE) and BBa_K3925007-NADH oxidase gene (nox).

In order to more intuitively reflect the expression of functional genes of the engineered strains E.coli pSB-BBa_K857000 and E.coli pSB-BBa_K3925009, we tested the enzymatic activity of various exogenous enzymes and the coenzyme NAD+ under the conditions of in vitro culture of different strains. content.

The results are shown in the figure. In the crude enzyme extracts of bacteria, E. coli 1917 basically did not show alcohol dehydrogenase, acetaldehyde dehydrogenase and NADH oxidase activities, and the content of the coenzyme NAD+ was extremely low; E. The ADH activity of coli pSB-BBa_K857000 was 47.91 ± 3.12 U/mL, the ALDH activity was 33.57 ± 2.59 U/mL, and NADH oxidase activity was not detected; while the ADH activity of E. coli pSB-BBa_K3925009 was 81.41 ± 3.64 U/mL mL, ALDH activity is 57.56 ± 1.48 U/mL, nox activity is 14.4 ± 2.29 U/mL, bacterial expression of ADH and ALDH enzyme activity is greatly increased, and the content of coenzyme NAD+ is also greatly increased compared with strain E.coli pSB-BBa_K857000. It shows that the expression of NAD synthase gene nadE and NADH oxidase gene nox can help increase the content of dehydrogenase coenzyme NAD in bacterial cells, thereby enhancing the degradation ability of alcohol dehydrogenase and acetaldehyde dehydrogenase.

literuture1

Alcohol use disorder (AUD) is a major global health concern (Peacock et al., 2018). There are considerable efforts being made to identify new molecular targets within the brain for the development of more effective therapies to treat this addictive disorder. As an approach in this direction, new research by Mews et al., 2019 published recently in Nature has demonstrated that the tertiary metabolite of alcohol (acetyl-CoA) is important in regulating ethanol’s effects in the brain and serves as a substrate in directly promoting histone acetylation, thereby regulating gene expression in the neurons and alcohol-related behaviors

Ethanol metabolism has previously been identified as an important factor in the toxic effects produced by ethanol consumption (Cederbaum, 2012). Ethanol is metabolized to acetyl-CoA through a three-step process, starting first with the oxidation of ethanol to acetaldehyde by alcohol dehydrogenase IB in the liver (Cederbaum, 2012). Other tissue-specific enzymes, such as alcohol dehydrogenase IA, are also important in this step. Acetaldehyde is then converted to acetic acid by aldehyde dehydrogenase 2, which is the rate-limiting step of alcohol metabolism. Finally, acetic acid is converted to Acetyl-CoA, where it enters the citric cycle and can be released as H2O and CO2. Acetaldehyde is a highly reactive species that induces oxidative stress, mitochondrial damage, and cytokine formation (Guo and Ren, 2010). Furthermore, build-up of acetaldehyde is often found in heavy drinkers, and individuals without functioning aldehyde dehydrogenase 2 have vasodilation, nausea, and dysphasia when alcohol is consumed (Cederbaum, 2012, Guo and Ren, 2010). Efforts to capitalize on this effect as a deterrent to alcohol consumption resulted in the use of disulfiram (Antabuse) in the clinic to limited efficacy. Furthermore, ethanol has been shown to affect a staggeringly large number of different organ systems (notably the liver and brain) and a substantial number of different cell-transduction pathways, including epigenetic processes (Cederbaum, 2012, Choudhury and Shukla, 2008, Pandey et al., 2017). Chronic ethanol exposure is known to contribute to many of the negative physiological symptoms of withdrawal (Koob and Volkow, 2016, Pandey et al., 2017).

Histone acetylation is one of the most studied epigenetic processes that controls gene transcription (Pandey et al., 2017). The effects of acute ethanol on the epigenome via histone acetylation appear to be involved in anxiolytic effects (Pandey et al., 2017). Several previous studies have demonstrated that acute ethanol has the ability to activate histone acetyltransferases (HATs) and inhibit histone deacetylases (HDACs) in the brain (Pandey et al., 2017; Figure 1). These properties may lead to increased histone acetylation (active epigenetic marks) that produces chromatin remodeling and changes in gene expression in the amygdala, a brain region responsible for comorbidity of anxiety and AUD (Pandey et al., 2008, Pandey et al., 2017). Previous research has demonstrated that different alcohols and their metabolites can also induce changes to histone acetylation in hepatocytes (Choudhury and Shukla, 2008).

Mews et al. have suggested that acetate coming from the liver directly binds to neuronal chromatin (Figure 1) and is then converted to acetyl-CoA via chromatin-bound acetyl-CoA synthetase 2 (ACSS2) (Mews et al., 2019). This appears to be another fascinating epigenetic mechanism involved in the action of ethanol. The current research elegantly combines metabolomics and RNA and ChIP sequencing to show that alcohol contributes to histone acetylation in the mouse brain. Using liquid-chromatography mass spectrometry, the authors demonstrate that a single intraperitoneal injection of deuterated ethanol into mice rapidly increases histone acetylation in the dorsal hippocampus (dHPC) and prefrontal cortex (as well as the liver), and this increase lasts about 8 h. The authors further demonstrate that this is regulated by chromatin-bound acetyl-CoA synthetase 2 (ACSS2). Interestingly, alcohol exposure produces more H3K9ac and H3K27ac peaks in dHPC at the genome-wide level, which is prevented by the knockdown of ACSS2. This manipulation also prevents ethanol-conditioned place preference, suggesting that ACSS2 is required for ethanol reward learning, and provides more experimental evidence that epigenetic mechanisms are required for learning and memory. Previous studies have shown that learning and memory crucially rely on histone deacetylase-2-mediated epigenetic processes (Guan et al., 2009), and this new evidence creates a clearer picture about how ethanol facilitates its rewarding properties via ACSS2-dependent histone acetylation (Mews et al., 2019).

Since both ethanol and its secondary metabolite are known to be involved in changes in gene expression, the authors also evaluated if there was significant overlap between genes upregulated by the addition of acetate (ex vivo) and ethanol (in vivo) using RNA sequencing. There was substantial overlap between genes induced by acetate and ethanol (830 genes). An additional 1,010 genes were upregulated by ethanol and 2,783 upregulated by acetate, suggesting that there are also effects of ethanol that are independent of an acetate-induced mechanism. While the authors did perform gene ontology (GO) analysis on genes induced by acetate, it would also be interesting to see what GO analysis was involved for genes that overlapped with exposure to ethanol and exposure to acetate. Also, it would be interesting to examine if acetate has any direct effects on other epigenetic players responsible for histone acetylation changes in the brain, such as HATs and HDACs.

Transgenerational epigenetic regulation by drugs of abuse has been an area of intense study, particularly in the field of alcohol abuse (Chastain and Sarkar, 2017). Fetal alcohol spectrum disorder (FASD) occurs when the fetus is harmed during prenatal alcohol exposure. The authors demonstrate that maternal exposure to alcohol also causes changes in histone acetylation in the fetal brain, and this may contribute to the distinctive facial features, learning disabilities, and psychiatric symptoms that characterize this disorder by causing epigenetic dysregulation of tightly controlled developmental pathways (Mews et al., 2019). In summary, this study helps to answer questions regarding how acute ethanol increases histone acetylation and contributes significantly to our understanding of epigenetic regulation produced by alcohol drinking. Previous studies have indicated that histone deacetylase pathways are crucial in alcohol withdrawal and dependence and could be acting as a responsive mechanism for epigenetic reprogramming (Pandey et al., 2008, Pandey et al., 2017). Several key questions remain, specifically how an ACSS2-dependent histone acetylation mechanism contributes to the withdrawal aspects and ethanol tolerance that are observed in both animal models of alcohol dependence and in clinical populations. It would be interesting to see an expansion of this research to explore these topics.

Acknowledgments

SCP is supported by National Institute on Alcohol Abuse and Alcoholism grants UO1AA-019971 , U24AA-024605 ( Neurobiology of Adolescent Drinking in Adulthood [NADIA] project), RO1AA-010005 , P50AA-022538 ( Center for Alcohol Research in Epigenetics ), and by the Department of Veterans Affairs (VA merit grant I01BX004517 & Senior Research Career Scientist award). J.P.B. is supported by a fellowship F32 AA027410 grant.

Reference

Pandey SC, Bohnsack JP. Alcohol Makes Its Epigenetic Marks. Cell Metab. 2020 Feb 4;31(2):213-214. doi: 10.1016/j.cmet.2020.01.008. PMID: 32023443; PMCID: PMC7162615.

Literature 2

The robustness of Saccharomyces cerevisiae in industrial fermentation processes, combined with fast developments in yeast synthetic biology and systems biology, have made this microorganism a popular platform for metabolic engineering (Hong and Nielsen, 2012). Many natural and heterologous compounds whose production from sugars is under investigation or already implemented in industry require acetyl-coenzyme A (acetyl-CoA) as a key precursor. Examples of such products include n-butanol, isoprenoids, lipids and flavonoids (Dyer et al., 2002, Koopman et al., 2012, Shiba et al., 2007, Steen et al., 2008, Veen and Lang, 2004).

Acetyl-CoA metabolism in S. cerevisiae is compartmented (Pronk et al., 1996, van Roermund et al., 1995). During respiratory growth on sugars, a substantial flux through acetyl-CoA occurs via the mitochondrial pyruvate dehydrogenase complex (Pronk et al., 1994). However, mutant analysis has shown that mitochondrial acetyl-CoA cannot meet the extramitochondrial requirement for acetyl-CoA in the yeast cytosol, which includes, for example, its use as a precursor for synthesis of lipids and lysine (Flikweert et al., 1999, van den Berg and Steensma, 1995). In this respect, it is relevant to note that S. cerevisiae does not contain ATP-citrate lyase, an enzyme that plays a major role in translocation of acetyl-CoA across the mitochondrial membrane in mammalian cells and in several non-Saccharomyces yeasts (Boulton and Ratledge, 1981). When sugars are used as the carbon source, cytosolic acetyl-CoA synthesis in S. cerevisiae occurs via the concerted action of pyruvate decarboxylase (Pdc1, 5 and 6), acetaldehyde dehydrogenase (Ald2, 3, 4, 5 and 6) and acetyl-CoA synthetase (Acs1 and 2) (Pronk et al., 1996). Heterologous, acetyl-CoA-dependent product pathways expressed in the S. cerevisiae cytosol exclusively depend on this ‘pyruvate dehydrogenase bypass’ for provision of acetyl-CoA. Indeed, overexpression of acetyl-CoA synthetase (ACS) from Salmonella enterica has been shown to lead to increased productivities of the isoprenoid amorphadiene by engineered S. cerevisiae strains (Shiba et al., 2007).

The ACS reaction involves the hydrolysis of ATP to AMP and pyrophosphate (PPi): Together with the subsequent hydrolysis of PPi to inorganic phosphate (Pi), this ATP consumption is equivalent to the hydrolysis of 2 ATP to 2 ADP and 2Pi. The resulting ATP expenditure for acetate activation can have a huge impact on the maximum theoretical yields of acetyl-CoA derived products. For example, the production of a C16 lipid from sugars requires 8 acetyl-CoA, whose synthesis via ACS requires 16 ATP. At an effective P/O ratio of respiration in S. cerevisiae of 1 (Verduyn, 1991), this ATP requirement for acetyl-CoA synthesis corresponds to 1 mol of glucose that needs to be respired for the synthesis of 1 mol of product.

In addition to the pyruvate-dehydrogenase complex, other reactions have been described in nature that enable the ATP-independent conversion of pyruvate into acetyl-CoA (Powlowski et al., 1993, Rudolph et al., 1968, Smith and Kaplan, 1980). Many prokaryotes contain an acetylating acetaldehyde dehydrogenase (A-ALD; EC 1.2.1.10) which catalyses the reversible reaction:

Although functional expression of bacterial genes encoding A-ALD in S. cerevisiae has been described in the literature, these studies focused on reductive conversion of acetyl-CoA to ethanol as part of a phosphoketolase pathway for pentose fermentation (Sonderegger et al., 2004) or as part of a metabolic engineering strategy to convert acetic acid to ethanol (Guadalupe Medina et al., 2010). Complete replacement of the native acetaldehyde dehydrogenases and/or ACS of S. cerevisiae by A-ALD, thereby bypassing ATP hydrolysis in the ACS reaction, has not been demonstrated. In many anaerobic bacteria and some eukaryotes (Stairs et al., 2011), pyruvate can be converted into acetyl-CoA and formate in the non-oxidative, ATP-independent reaction catalysed by pyruvate-formate lyase (PFL; EC 2.3.1.54):

PFL and PFL-activating enzyme (PFL-AE; EC 1.97.1.4) from Escherichia coli have previously been expressed in S. cerevisiae (Waks and Silver, 2009). Although formate production by this oxygen-sensitive enzyme system was demonstrated in anaerobic yeast cultures, its impact on cytosolic acetyl-CoA metabolism has not been investigated.

To gain the full potential benefit of ATP-independent cytosolic acetyl-CoA synthesis, the implemented heterologous pathways expressed in S. cerevisiae should, ideally, completely replace the ACS reaction. In wild-type strain backgrounds, deletion of both ACS1 and ACS2 is lethal (van den Berg and Steensma, 1995) and, during batch cultivation on glucose, presence of a functional ACS2 gene is essential (van den Berg and Steensma, 1995) because ACS1 is subject to glucose repression (van den Berg et al., 1996) and its product is inactivated in the presence of glucose (de Jong-Gubbels et al., 1997). Moreover, it has been proposed that Acs2, which was demonstrated to be partially localized in the yeast nucleus, is involved in histone acetylation (Takahashi et al., 2006). Involvement of Acs isoenzymes in the acetylation of histones and/or other proteins might present an additional challenge in replacing them with heterologous reactions, if this includes another mechanism than merely the provision of extramitochondrial acetyl-CoA.

The goal of this study is to investigate whether the heterologous ATP-independent A-ALD and PFL pathways can support the growth of acs1 acs2 mutants of S. cerevisiae by providing extramitochondrial acetyl-CoA and to study the impact of such an intervention on growth, energetics and cellular regulation. To this end, several heterologous genes encoding A-ALD and PFL were screened by expression in appropriate yeast genetic backgrounds, followed by detailed analysis of S. cerevisiae strains in which both ACS1 and ACS2 were replaced by either of the alternative reactions. The resulting strains were studied in batch and chemostat cultures. Furthermore, genome-wide transcriptional responses to these modifications were studied by chemostat-based transcriptome analysis of engineered and reference strains.

Reference

Nakazawa M. C2 metabolism in Euglena. Adv Exp Med Biol. 2017;979:39-45. doi: 10.1007/978-3-319-54910-1_3. PMID: 28429316.

Sequence and Features